Apparatus, systems and methods for generating an emotional-based content recommendation list

ABSTRACT

Media content recommendation systems and methods are operable to recommend one or more media content events to a user based on identified changes in the user&#39;s emotional state during a life event that is experienced by the user.

PRIORITY CLAIM

This patent application is a Continuation of U.S. Non-Provisional patentapplication Ser. No. 15/833,370, filed Dec. 6, 2017, entitled“APPARATUS, SYSTEMS AND METHODS FOR GENERATING AN EMOTIONAL-BASEDCONTENT RECOMMENDATION LIST”, the contents of which is incorporatedherewith in its entirety.

BACKGROUND

Many prior art systems and processes determine user content preferencesbased on the user's prior viewing pattern and/or history. Typically,content (interchangeably referred to herein as a media content event)presents theme-based visual and audio content to a user for theirenjoyment and/or for informative purposes. Examples of such theme-basedcontent includes movies, films, serial programming, sporting events,documentaries, newscasts, religious programs, commercials (typically ofshort duration with advertising content), or the like. Serialprogramming may present a continuing plot and/or theme, often with thesame cast of actors, in a sequential episode-by-episode basis that isavailable periodically. Advertisements, commercials or the like may beinterspersed within the media content event. Content may also be audioonly content, such as a song, concert, commentary, or the like.

As is well known in the arts, the user's prior viewing pattern and/orhistory can be analyzed to identify characteristics of the content thatthe user has previously viewed. Then, a comparison of the identifiedcharacteristics of the prior viewed content may be used to identifypatterns of the user's viewing habits and/or preferences such that oneor more particular genres of favored content can be identified. A genreis a category of artistic composition, as in audio visual content, musicor literature, that is characterized by similarities in form, style,and/or subject matter. Such identified genre can then be defined as auser preference for that particular user.

The benefits of knowing user preferences are well known. For example,once user-preferred content that the user has not yet consumed isidentified, the user can be informed about the availability of theidentified user-preferred content. For example, a future scheduledbroadcast of one or more of the identified user-preferred content can beindicated to the user who may then choose to view and/or record thecontent when the content is broadcast. Some systems may evenautomatically configure a user device to record the identifieduser-preferred content during the broadcast of the content.Alternatively, or additionally, one or more of the identifieduser-preferred content may be available on a pay for view basis, arental, and/or on a premium based service. Here, the user may decide topay to view and/or subscribe to a service to obtain access to theidentified user-preferred content.

Such prior art systems and processes identify user preferences based onhistorical viewing patterns or activities of the user. That is, theprior art systems and processes determine user genre preferences basedon “what” content the user has previously consumed (interchangeablyreferred to herein as “viewing” or the like).

A deficiency in such prior art systems and processes is that there is alikelihood in failing to identify particular content that the user mayotherwise be interested in viewing when that content does not relate toan identified user genre preference determined from “what” content theuser has previously consumed. More particularly, the prior art systemsand processes have not determined “why” the user may prefer suchgenre-based content. That is, the user's personal experiences have notbeen taken into account during the determination of the user preference.

To illustrate, consider a user who has an identified user genrepreference for action type content (action movies, action serialprograms, or the like). This particular identified user genre preferenceis based upon the user having previously consumed a plurality of actiongenre content. Further, consider situations where the prior art systemsand processes have not determined that the user might like to consume amedia content event associated with a romantic comedy genre (since theuser has not previously viewed, or has only previously viewed arelatively small number of, romantic drama genre content). Here, it isvery likely that the prior art systems and processes may fail toidentify and recommend a particular media content event that isclassified, at least in part, to be a romantic drama genre media contentevent because this romantic comedy genre media content event is notassociated with the action genre content that has been determined to bea user genre preference. However, it may be that the user may actuallywant to consume this particular media content event even though it isnot one of the user's genre preferences.

Further, the particular media content event that is not recommended mayhave one or more story elements that may be of high interest to theuser. A story element is a textual description of a thematic aspect ofthe media content event that includes the following components: thecharacters, the setting, the plot, the conflict and the resolution.Thus, the particular media content event would not be recommend to theuser even though that particular media content event may have one ormore story elements that are of high interest to the user.

Accordingly, there is a need in the art to improve prior art systems andprocesses that are limited to identifying user preferences based on“what” particular content the user has previously consumed.

SUMMARY

Media content recommendation systems and methods are operable torecommend one or more media content events to a user based on identifiedchanges in the user's emotional state during a life event that isexperienced by the user.

BRIEF DESCRIPTION OF THE DRAWINGS

Preferred and alternative embodiments are described in detail below withreference to the following drawings:

FIG. 1 is a block diagram of an embodiment of the user contentpreference identification system;

FIG. 2 is a block diagram of an embodiment of an emotional state monitor(ESM);

FIG. 3 is a hypothetical image of a duration of EEG information providedby an Electroencephalography (EEG) sensor;

FIG. 4 is a block diagram of an example user content preferenceidentification device; and

FIG. 5 is a block diagram of an embodiment of the user contentpreference identification system that is operable to control a mediadevice.

DETAILED DESCRIPTION

FIG. 1 is a block diagram of an embodiment of the user contentpreference identification system 100. The exemplary user contentpreference identification system 100 comprises an emotional statemonitor (ESM) 102, a plurality of electronic portal devices 104, and atleast one user content preference identification device 106.

An exemplary embodiment of the user content preference identificationsystem 100 identifies at least one media content event based on theuser's prior viewing emotional experiences and/or based on the user'spast life experiences that elicited a change in the user's emotionalstate. That is, embodiments of the user content preferenceidentification system 100 initially determine “why” a user may have anemotional preference, emotional dislike, and/or emotional disinterestbased on the user's past emotional experiences. The user's emotionalpreferences, dislikes, and/or disinterests may be based, in part, on theuser's emotional experience when viewing a particular media contentevent. Alternatively, or additionally, the user's emotional preferences,dislikes, and/or disinterests may be determined, in part, based on theuser's real world life experiences that are associated with the user'semotions experienced during a real world event that they have personallyexperienced.

Then, embodiments of the user content preference identification system100 identify one or more user content preferences, user contentdislikes, and/or user content disinterests based on the user's emotionalexperiences that define their emotional preferences, dislikes, and/ordisinterests. Based on the user content preferences, user contentdislikes, and/or user content disinterests that are determined from theuser's emotional preferences, dislikes, and/or disinterests, embodimentsof the user content preference identification system 100 then identifyone or more media content events that have one or more characteristicsthat are related to the cause of the user's emotional preferences,dislikes, and/or disinterests. Preferably, the identified media contentevents have not yet been consumed by the user (that is, the identifiedmedia content events have not yet been viewed by the user).

The identified media content events that may be of particular interestto the user (based on their determined emotional content preferences)that the user may wish to consume are then recommended to the user.Conversely, one or more of the identified media content events may be oflittle to no interest (based on their determined content disinterests),and/or may be disfavored or disliked by the user (based on theirdetermined content dislikes). Here, recommendations may optionallyidentify media content events that are of little to no interest to, oreven likely to be disliked by, the user. In some implementations, acombination of a plurality of different user content preferences,content dislikes, and/or content disinterests may be used to identify aparticular recommended media content event.

The ESM 102 is configured to monitor biometrics of the user (who iswearing the ESM 102). The detected user biometrics indicate a currentemotional state of the user. In an example embodiment, the ESM 102includes an Electroencephalography (EEG) sensor 108. EEG is anelectrophysiological monitoring method to record electrical activity ofthe user's brain. The EEG sensor 108 is typically noninvasive, with oneor more electrodes (not shown) placed along the inner surface of the ESM102 so as to be in physical contact with the user's scalp. The EEGsensor 108 measures voltage fluctuations resulting from ionic currentwithin the neurons of the brain. The detected ionic currents areindicative of the user's emotional state. Embodiments of the usercontent preference identification system 100 are able to identifyevent-related changes in the ionic current potentials based on aspectral analysis of the ionic current content of the EEG by analyzing,in the frequency domain, the type of neural oscillations (popularlycalled “brain waves”) that are observed in EEG signals detected by theEEG sensor 108. Alternatively, or additionally, other types of biometricsensors may be used to detect the emotional state of the user.

The ESM 102 further includes at least one image capture device 110 thatis oriented in an outward direction and in alignment with the user'seyes. The image capture device(s) 110 captures images that correspond tothe visual field of view that is currently being seen by the user.Accordingly, embodiments of the user content preference identificationsystem 100 are configured to obtain image information that can be usedto identify one or more objects that are in the field of view of theuser's current vision. Preferably, the image capture device 110 isoperable to capture real-time video image data. Alternatively, the imagecapture device 110 may capture a series of still images (each separatedby some duration).

In some embodiments, multiple image capture devices 110 may be used toprovide a sufficiently large field of view for the analysis of thecaptured image information when objects that the user has seen areidentified. Alternatively, or additionally, the additional image capturedevices 110 may be used to capture images that are outside of the fieldof view of the user, such as behind the user, above the user, below theuser, and/or to the sides of the user. Some embodiments may employ a360° camera or the like. The use of a plurality of different imagecapture devices 110 oriented in differing directions enhances theability of the user content preference identification system 100 to moreaccurately discern objects that may have elicited a currently detectedemotional reaction from the user, particularly if the objects are notactually being viewed by the user.

The information from the EEG sensor 108 and the captured imageinformation from the image capture device 110 each include timeinformation that is used to synchronized the EEG sensor 108 informationand the image capture device 110 information with each other. Forexample, a time stamp or the like may be used to identify a relativetime of information acquisition by the EEG sensor 108 and the imagecapture device 110. The time information may optionally indicate realtime. Accordingly, when the user experiences an emotional event (asindicated from an increased EEG activity level, for example), objectsseen by the user at that same time, or just before a detectable changein the users' emotional state, may be identified from the captured imageinformation provided by the image capture device 110. Then, an inferencemay be made by the user content preference identification system 100that a particular object, when viewed by the user, is likely to elicit aparticular emotional response from the user.

The ESM 102 may optionally include at least one microphone 112. Themicrophone(s) 112 detects sounds that are being heard by the user.Accordingly, embodiments of the user content preference identificationsystem 100 can obtain audio information that can be used to identify oneor more sounds in the immediate vicinity of the user that were heard bythe user at that same time, or just before a detectable change in theusers' emotional state. Some embodiments may have a plurality ofmicrophones 112 to detect the sounds that are being heard by the user.Differences in sound detected at different ones of microphones 112 maybe used to compute (triangulate) the location and/or direction of thesource of the detected sound. In some embodiments, one or more of themicrophones may be directional microphones that detect sound in alimited orientation from the microphone 112 so that the location and/ordirection of the source of the detected sound.

The audio information from the microphone 112 may also include timeinformation that is used to synchronized the EEG sensor 108 informationand the image capture device 110 information with the audio informationprovided by the microphone 112. For example, a time stamp or the likemay be used to identify a relative time of information acquisition bythe microphone 112 (relative to the information provided by the EEGsensor 108 and the image capture device 110). The time information mayoptionally indicate real time. Accordingly, when the user experiences anemotional event (as indicated from an increased EEG activity level, forexample), sounds heard by the user at that same time may be identifiedfrom the audio information provided by the microphone 112. Then, aninference may be made by the user content preference identificationsystem 100 that a particular sound, when heard by the user, is likely toelicit a particular emotional response from the user.

At least one of the portals 104, such as the example portal 104 a, iscommunicatively coupled to the ESM 102. Preferably, a portal 104 iscommunicatively coupled to the ESM 102 via a wireless signal 114, suchas an infrared or radio frequency signal. Alternatively, oradditionally, a wire-based connector may be used to communicativelycouple a portal 104 to the ESM 102.

The receiving portal 104 is communicatively coupled to the user contentpreference identification system 100 via a suitable communicationnetwork 116. In some embodiments, a plurality of portals 104 aregeographically distributed about a region of interest that the user islikely to be located in. The plurality of portals 104 increase thelikelihood that the user's ESM 102 is communicatively coupled to atleast one portal 104 at substantially all times. In some embodiments,when a plurality of portals 104 are concurrently receivingcommunications from the ESM 102, a selected one of the portals 104communicated the received information to the user content preferenceidentification device 106. If the user is moving, wherein a currentlycommunicating portal 104 becomes out of range of the ESM 102, thencommunications can be handed off to another receiving ESM 102 (suchcommunication hand off processes are well known in the arts). That is,the information provided by the ESM 102 can then be received by at leastone portal 104 regardless of the user's current geographic location.

The information received from the ESM 102 may then be communicated fromthe portal 104 to the user content preference identification device 106where an analysis of the user's emotional information is processed suchthat the user's emotional preferences, emotional dislikes, and/oremotional disinterest is determined. The portal 104 may be a specialpurpose device configured to communicatively couple to one or more ESMs102. Alternatively, or additionally, the portal 104 may be a legacymobile device (such as a smart phones, cellular phones, notebookcomputers, laptop computers, personal computers, wearable devices, orpersonal device assistants) a cell tower device of a cellular telephonesystem, an internet WiFi hot spot, a blue tooth receiver, or anothersuitable legacy device or system that enables the ESM 102 to communicatethe user's emotional state information, captured image information,and/or detected audio information to the user content preferenceidentification device 106.

In the various embodiments, the user content preference identificationdevice 106 may concurrently be communicatively coupled to a plurality ofdifferent portals 104, and thus to a plurality of different ESMs 102.Accordingly, information from a plurality of ESMs 102 being worn bydifferent users can concurrently provide information to the user contentpreference identification system 100 so that a the emotional state of aplurality of different users are monitored.

Summarizing, the ESM 102 continuously captures, in real time,information that is associated with, and that is indicative of, theuser's current emotional state. Further, information pertaining to theuser's life experience is captured by the ESM 102 as image informationcorresponding to what the user is seeing and/or audio informationcorresponding to sound that the user is hearing. The informationassociated with the user's emotional state and their life experience iscommunicated from the ESM 102 to the portal 104, and then to the usercontent preference identification system 100. This information isanalyzed, and over time, the user content preference identificationdevice 106 learns “why” a user may have an emotional preference,dislike, and/or disinterest about a life experience of a real worldevent and/or a viewed media content event.

The user content preference identification system 100 may then identifyone or more emotional-based user content preferences, emotional-baseduser content dislikes, and/or emotional-based user content disinterestsbased upon anticipated emotional responses of the user if that mediacontent event is consumed by the user. These identified emotional-basedcontent preferences, dislikes, and/or disinterests are then used toidentify one or more media content events that the user may be informedabout. Preferably, the identified media content events have not yet beenconsumed (viewed) by the user. The identified media content events maythen be indicated to the user as a recommended media content event(which may be a recommendation to view if some aspect of the mediacontent event corresponds to a user's emotional preference, arecommendation to not view if some aspect of the media content eventcorresponds to a user's emotional dislike, or a recommendation todisregard if some aspect of the media content event corresponds to auser's emotional disinterest).

Preferably, the recommended media content events are communicated to anelectronic media device 118 with a display. The recommended mediacontent events can be visually indicated to the user on the displayusing any suitable textual format and/or other visual format. Thedisplay may be a component of, or communicatively coupled to, smartphones, cellular phones, notebook computers, laptop computers, personalcomputers, wearable devices, or personal device assistants.Alternatively, or additionally, the recommended media content events arecommunicated to an electronic media device 118 that is communicativelycoupled to a media presentation system 120 with a display, wherein therecommended media content events can be indicated to the user on thedisplay. The recommendations may be communicated to the media device 116via the communication network 116.

In response to viewing the recommended media content events on thedisplay, the user may choose to consume one or more of the recommendedmedia content events. That is, the user may choose to view and/or recordone or more of the recommended media content events (when at least oneattribute of the recommended media content event corresponds to a user'semotional like). Alternatively, the user may choose to not consume oneor more of the recommended media content events, particularly when theuser content preference identification system 100 indicates to the userthat they are likely to dislike the recommended media content events(when at least one attribute of the recommended media content eventcorresponds to a user's emotional dislike) and/or are likely to bedisinterested in the recommended media content events (when at least oneattribute of the recommended media content event corresponds to a user'semotional disinterest).

Further, embodiments of the user content preference identificationsystem 100 may optionally indicate “why” the media content event hasbeen recommended to the user. That is, supplemental information may bepresented to the user that identifies or describes the previous and/oranticipated user emotional experiences that are related tocharacteristics of a particular recommended media content event. Thus,the supplemental information may assist the user in making a moreinformed decision when deciding if they wish to consume (view and/orrecord) or ignore the recommended media content event

An example media device 118 may be a set top box that is configured toreceive one or more media content streams 122 from a content provider.Other non-limiting examples of media devices 102 include smart phones,cellular phones, notebook computers, laptop computers, personalcomputers, wearable devices, or personal device assistants (PDAs).

In some instances, the media device 118 may be embodied with a portal104. For example, the illustrated media device 118 includes the portal104 b that, when in proximity to the ESM 102, receives the emotional,image, and audio information being captured by the ESM 102. The mediadevice 118 may then communicate the information received from the ESM102 to the user content preference identification device 106 via thecommunication network 116. As another non-limiting example, smartphones, cellular phones, notebook computers, laptop computers, personalcomputers, wearable devices, or personal device assistants may be usedas a portal 104.

The communication network 116 is illustrated as a generic communicationsystem. In one embodiment, the communication network 116 comprises acellular telephone system, such as a radio frequency (RF) wirelesssystem. Accordingly, the media device 118, a portal 104, and/or the usercontent preference identification device 106 may each optionally includea suitable transceiver to enable wireless communications over thecommunication network 116. Alternatively, the communication network 116may be a telephony system, the Internet, a Wi-fi system, a microwavecommunication system, a fiber optics system, an intranet system, a localaccess network (LAN) system, an Ethernet system, a cable system, a radiofrequency system, a cellular system, an infrared system, a satellitesystem, or a hybrid system comprised of multiple types of communicationmedia. Additionally, embodiments of the media device 118, a portal 104,and/or the user content preference identification device 106 may beimplemented to communicate using other types of communicationtechnologies, such as but not limited to, digital subscriber loop (DSL),X.25, Internet Protocol (IP), Ethernet, Integrated Services DigitalNetwork (ISDN) and asynchronous transfer mode (ATM). Also, embodimentsof the media device 118, a portal 104, and/or the user contentpreference identification device 106 may be configured to communicateover combination systems having a plurality of segments which employdifferent formats for each segment that employ different technologies oneach segment.

FIG. 2 is a block diagram of an embodiment of an exemplary ESM 102. TheESM 102 comprises a processor system 202, a user emotional state sensor108, at least one image capture device 110, at least one microphone 112,a memory 204, an optional information buffer 206, an optionaltransceiver 208, an optional eye orientation sensor 210, an optionalclock 212, and an optional connector 214. Other embodiments of the ESM102 may include more components (not shown) and/or may include fewercomponents than those shown in FIG. 2.

Preferably, the components of the ESM 102 are enclosed in a structure orenclosure that is wearable by the user. In a non-limiting exampleembodiment, the ESM 102 resembles a pair of glasses that are worn on thehead of the user. Another example may be a helmet-like device thatencloses the user's head, such as a virtual reality head set, a headmounted display, or the like. Any suitable structure or enclosure forthe components of the ESM 102, including multiple enclosures thatcontain different or common components, may be used by alternativeembodiments of the user content preference identification system 100.The enclosure of the ESM 102 may optionally include other components,devices and/or systems that perform other tasks and functions that arenot related to the user content preference identification system 100.

The EEG sensor 108 includes one or more sensors that are configured todetect brain wave activity of the user in real time. The detected brainwave activity is correlated to the emotional state of the user. Forexample, if the user enters into an excited state that corresponds toanticipation, surprise, joy, sadness, disgust, trust, anger, and/orfear, the brain wave activity information provided by the EEG sensor 108can be analyzed to ascertain the particular state of the user's emotion(anticipation, surprise, joy, sadness, disgust, trust, anger, and/orfear) and the degree (amplitude) of the emotion on the part of the user.Supplemental information, such as an explicit input by the user, may beused to improve the determination of the particular emotional state ofthe user.

Other embodiments may alternatively, or additionally, use other types ofbiometric sensors that sense various characteristics of the user.Example biometric sensors may provide information that includes, but isnot limited to, blood pressure information, heart rate information, bodytemperature information, and/or eye pupil dilation information. Anysuitable biometric information that correlates to the emotional state ofthe user may be collected and analyzed by the various embodiments of theuser content preference identification system 100. Such additionalinformation may improve the accuracy and reliability of the determineduser's emotional state.

Some embodiments of the ESM 102 include an eye orientation sensor 210.The eye orientation sensor 210 is an electronic device or system, suchas a small image capture device, that is oriented towards at least oneeye of the user who is wearing the ESM 102. The eye orientation sensor210 provides eye orientation information that is used to determine thecurrent orientation of the user's eye(s). The determined eye orientationcan be used to better locate an object that the user is looking towardsat any given instant in time. For example, if the user is looking to theleft, then objects identified in the left hand side of the imagescaptured by the image capture device(s) 110 are likely to be theparticular object that the user was viewing. Similar to the timeinformation used to coordinate the information provided by the EEGsensor 108, the image capture device(s) 110 and the microphone(s) 112,time information is also provided for the information acquired by theeye orientation sensor 210. Thus, determined eye orientation of the usercan be synchronized with the information provided by the EEG sensor 108,the image capture device(s) 11, and the microphone(s) 112. The ESM logic218 may optionally include any suitable eye orientation determinationlogic.

Timing information is used to synchronize the information received fromthe EEG sensor 108 with the image information received from the imagecapture device 110 and the audio information received from themicrophone 112. The timing information may be provided by the clock 212.Alternatively, one or more of the EEG sensor 108, the image capturedevice 110, and/or the microphone 112 may have their own clock devicethat provides timing information. The time information provided by theclock 212 may be in real time. Alternatively, or additionally, the clockinformation provided by the clock 212 may be a relative indicator thatindicates time relative to the information that is concurrently receivedfrom the image capture device(s) 110, the microphone(s) 112, the EEGsensor 108 and/or the eye orientation sensor 210.

Time information received from the clock 212 may be incorporateddirectly into the emotional state information received from the EEGsensor 108. The time information is used to identify the time of anidentifiable emotional state of the user and/or the time that the user'semotional state has changed. Time information received from the clock212 may also be directly incorporated into the captured imageinformation that is received from the image capture device 110. The timeinformation is used to identify the time of capture of portions of thevideo, and/or the time of capture of individual still images or imageframes of a video. Alternatively, or additionally, time informationreceived from the clock 212 may be directly incorporated into the audioinformation provided by the microphone 112. Accordingly, when theemotional state information, the captured image information, and thedetected audio information is analyzed by embodiments of the usercontent preference identification system 100, the information can besynchronized together so that the real life experience of the user maybe identified with a higher degree of accuracy and reliability.

Alternatively, the time information may be saved concurrently withcorresponding portions of the received information from the imagecapture device(s) 110, the microphone(s) 112, the EEG sensor 108 and/orthe eye orientation sensor 210. For example, a relational databaseapproach may be used to define time bins or the like that concurrentlystores received portions of the information from the image capturedevice(s) 110, the microphone(s) 112, the EEG sensor 108 and/or the eyeorientation sensor 210, wherein the time information provided by theclock 212 identifies the time associated with the bin. Any suitable timecorrelation process may be used by the various embodiments so that theinformation received from the image capture device(s) 110, themicrophone(s) 112, the EEG sensor 108 and/or the eye orientation sensor210 can be synchronized together.

In some embodiments, the information buffer 206 receives and storesinformation from the image capture device(s) 110, the microphone(s) 112,the EEG sensor 108, the eye orientation sensor 210, and/or otherbiometric sensors. Here, the acquired information is temporarily stored(interchangeably referred to herein as being buffered or buffering) intothe information buffer 206 for at least a predefined duration.

One skilled in the art appreciates that life events that affect theuser's emotional state are likely to be experienced prior to theoccurrence of a change in the user's emotional state. For example, ifthe user becomes frightened, “whatever life event” that caused the userto become frightened necessarily had to occur prior to the time that theuser experienced their frightened emotional state. To illustrate, assumethat a loud, brief and unexpected noise occurs in close proximity to theuser. The user was most likely not in a frightened emotional state priorto the occurrence of the loud and brief noise. Further, at the preciseinstant in time of the occurrence of the loud and brief noise, the userwas most likely not in a frightened emotional state. Only after theoccurrence of the loud and brief noise does the user enter into thefrightened emotional state because some duration of time is required forthe user to audibly hear and discern the noise, and then react to theirhearing of the noise. That is, the user becomes frightened only afterhearing the loud and brief noise. This duration (time delay) between theoccurrence of an event experienced by the user (visual, tactile and/orauditory) and the onset of a change in the user's emotional state isdefined herein as a perception time delay.

Because of this inherent perception time delay in “whatever” life eventthat elicits an emotional state in the user, the information provided bythe image capture device 110 and/or the microphone 112 must be availableto the user content preference identification system 100 so that thecause of the user's emotional state can be determined. Accordingly, inembodiments that include the information buffer 206, informationprovided by the image capture device(s) 110, the microphone(s) 112,and/or the EEG sensor 108 are buffered (temporarily stored) into theinformation buffer 206. The stored information is retained for at leastsome predefined duration. Any suitable memory medium now known or laterdeveloped may be used to buffer the received information for sometemporary duration.

In such embodiments that include the information buffer 206, theprocessor system 202 (executing the ESM logic 216 that has beenretrieved from the memory 204) monitors the emotional information (thedetected brain wave activity) received from the EEG sensor 108. When asignificant change in the user's emotional state is detected (asindicated by a significant change in the detected brain wave activity ofthe user), the processor system notes the time of the occurrence of thechange in the emotional state of the user. Then a duration of time canbe defined that encompasses the time of the occurrence of the change inthe emotional state of the user (a time before and a time after the timeof the occurrence of the change in the emotional state of the user).This determined duration (defined by the determined before and aftertimes) is used by the processor to retrieve a corresponding duration ofbuffered information from the EEG sensor 108, the image capturedevice(s) 110, the microphone(s) 112 that has been stored in theinformation buffer 206.

In some embodiments that omit the information buffer 206, theinformation from the image capture device(s) 110, the microphone(s) 112,and/or the EEG sensor 108 are communicated from the ESM 102 to theportal 104 in real time. The information is then communicated to theuser content preference identification device 106. The receivedinformation is then buffered or is otherwise temporarily stored by theuser content preference identification device 106. Alternatively, oradditionally, the received information from the ESM 102 may be storedfor a longer duration, and even stored permanently, in a persistentmemory medium at the user content preference identification device 106or at another suitable memory system or device.

The ESM 102 preferably includes a transceiver 208 that communicativelycouples the ESM 102 with at least one portal 104. In the variousembodiments, transceiver 208 is a communication device or systemconfigured to receive and transmit radio frequency (RF) signals. It isappreciated that any suitable transceiver device or system may be used,and that the transceiver 208 may have a variety of components thereinwhich are not described or illustrated herein for brevity. For example,but not limited to, the transceiver 208 may include as components areceiver and a transmitter device or system. Further, such componentsthemselves may be separate devices or systems. Alternatively, oradditionally, the ESM 102 may include a wire-based connector 214 thatenables the ESM 102 to communicatively couple to a portal 104 using awire type connector (not shown).

The ESM logic 218 includes communication logic that enables the ESM 102to communicatively coupled to a plurality of different types of portals104 using different communication formats via the transceiver 208 and/orthe connector 214. In some situations, the user may select a particularportal 104 that the ESM 102 will be communicatively coupled to. Forexample, the ESM may be an augmented reality device that has beencommunicatively coupled to a media device 118 (having the portal 104 b)via a view wire-based connector (using the connector 214), or via awireless signal (using the transceiver 208). The ESM logic 218 may atother times enable the ESM 102 to wirelessly connect to a portal 104that is configured to communicate over a cellular communication network116. The ESM logic 218 may further include logic that automaticallysearches for one or more available portals 104, identify and select apreferred portal 104, and then establish a communication link 114 tothat selected portal 104.

FIG. 3 is a hypothetical image of a stream of EEG information 302provided by the EEG sensor 108. Here, each of the brain wave lines 304corresponds to an output of one of the sensors of the EEG sensor 108.Time is illustrated and is referenced from the earliest time being atthe right hand side of the EEG information 302.

One skilled in the art appreciates that for the earlier first duration306, the user was likely in a relatively relaxed and/or stable emotionalstate, as evidenced by the relatively flat brain wave lines 304 duringthat duration 306. During the later second duration 308, one skilled inthe art appreciates that the user has likely transitioned into arelatively higher state of emotion, as evidenced by the relatively largeand numerous spikes in the brain wave lines 304 during that duration 308(interchangeably referred to herein as the emotional response duration308).

Further, one skilled in the art appreciates that because of the inherentperception time delay corresponding to the time or duration required torealize the change of emotional state of a user after the occurrence ofthe life event (or stimulus) that cause the change in emotional state,that it is likely that during the duration 310, no particular eventoccurred that would initiate a change in the user's emotional state(since the change in emotional state is not apparent during theimmediately following later duration 312). Rather, one skilled in theart appreciates that some particular life event initially started tooccur during the duration 312 (interchangeably referred to herein as alife event occurrence duration 312) that initiated the change in theuser's emotional state (as evidenced during the increased activity ofthe brain wave lines 304 occurring during the later duration 308). Thelife event occurring during the duration 312 may last any duration, andmay or may not end prior to the detected change in the user's emotionalstate.

In the various embodiments, a duration 312 that immediately precedes anincrease in activity of the brain wave lines 304 determinable for theduration 308 (that is associated with a change in the user's emotionalstate) is predefined. The predefined duration 312 is defined so that theinitial occurrence of the life event is highly likely to have beeninitiated at some point in time within the duration 312. The predefinedduration 312 may be specified by the operators of the user contentpreference identification system 100 during the initial configuration ofthe ESM 102, though the predefined duration 312 may be changed at anysuitable later time. For example, a duration of ten seconds, thirtyseconds, a minute, two minutes, several minutes or any other suitablepredefined duration may be used for the predefined duration 312.

In response to identifying and/or detecting the initiation of a changein the user's emotional state (during the later occurring duration 308),the information previously acquired by the EEG sensor 108, the imagecapture device(s) 110, the microphone(s) 112, and/or the eye orientationsensor 210 (and the associated time, such as provided from the clock212) begins to be accessed for detailed analysis. As described herein,the information was initially saved into the information buffer 206and/or was streamed out to the user content preference identificationdevice 106 as the information was being acquired.

The buffered information is saved until the brain wave activity lines304 tend to show that the user is no longer experiencing a change intheir emotions, such as at the end of the duration 308. At the end ofthe duration 308, the brain wave lines return to a relatively flat orstable level, as illustrated during the duration 316. The start of theduration immediately follows the end of the duration 308. In an exampleembodiment, the duration 308 may be a variable duration that is based onits start and concluding with the start of the duration 316.Alternatively, the duration 308 may be a predefined duration that islikely to have captured all of, or substantially all of, the user'semotional state change as indicated by the increased activity in thebrain wave lines 304.

Here, embodiments of the user content preference identification system100 will have saved information acquired from the EEG sensor 108, theimage capture device(s) 110, the microphone(s) 112, and/or the eyeorientation sensor 210 during the duration 314, interchangeably referredto herein as the life event duration 314. The duration 314 correspondsto the sum of the predefined duration 312 and the duration 308characterized by the higher level of brain wave activity.

Accordingly, the information acquired by the EEG sensor 108, the imagecapture device(s) 110, the microphone(s) 112, and/or the eye orientationsensor 210 (and the associated time information, such as provided fromthe clock 212) is accessed from the start of the duration 312 to the endof the duration 308. That is, the information acquired during theduration 314 is accessed and then saved for detailed analysis.

A threshold-based system may be used by some embodiments to analyze thebrain wave lines 304 to identify the onset (start) of an emotional statechange and the end of an emotional state change. When the level ofactivity of a brain wave line 304 exceeds the value of an onset brainwave activity threshold 318, then embodiments of the user contentpreference identification system 100 determine that the onset of anemotional state change is occurring. In some embodiments, a predefinednumber of the plurality of brain wave lines 304 must exhibit an increasein the activity levels over the onset threshold value 318 before theuser content preference identification system 100 determines that anonset of an emotional state change has occurred. Any suitable number ofbrain wave lines 304 may be defined to determine the onset of theemotional state change.

Depending upon the physical location of the particular EEG sensor thatacquires information that generates a particular brain wave line 304,those particular brain wave lines 304 may be given a greater weightingfactor and/or a lower onset threshold value 318 to indicate that thesebrain line waves 304 are more likely to be indicative of an onset of anemotional state of the user. For example, one skilled in the artunderstands that particular regions of the human brain are associatedwith different functions. Those regions of the human brain are known tobe associated with emotions, and such regions may be relatively close toa particular EEG sensor (such that that particular EEG sensor picks upchanges in brain activity in that region of the human brain). Theinformation acquired by a sensor in close proximity to the area of thebrain associated with emotions may be given more importance (via agreater weighting and/or a lower onset threshold 318) in thedetermination of a change (onset) in the emotional state of the user. Incontrast, some regions of the human brain are known to be associatedwith motor functions (which, presumably, are not as relevant toemotions). Accordingly, information acquired by a sensor in closeproximity to those areas of the brain that are associated with motorfunctions may be given less importance (via a lower weighting and/or ahigher onset threshold 318) in the determination of a change in theemotional state of the user.

The end of the duration 308 (corresponding to an end in the change ofthe user's emotional state) may be similarly determined by anotherpredefined threshold 320. When the value of movement in the brain wavelines 304 drops below the value of the threshold 320. Since after theend of the duration 308, the brain wave lines 304 (or at least tomepredefined number of brain wave lines 304) have returned to a relativelyflat or stable level that is less than the threshold 320, the end of theduration 308 is then identifiable by embodiments of the user contentpreference identification system 100. When determining the end of theemotional event, embodiments may use different weighting and/orthresholds 320 for particular ones of the brain wave lines 304.

One skilled in the art appreciates that the amount of data correspondingto the information acquired by the ESM 102 that has been stored in theinformation buffer 206 is ultimately limited by the storage capacity ofthe memory medium of the information buffer 206. At some point in timeafter the buffering of the acquired information into the informationbuffer 206, if no life event has been detected (based on an activitychange in the brain wave lines 304), then the earlier acquiredinformation may be overwritten, deleted, erased or otherwise discarded.For example, if no significant change in the brain wave lines 304 duringthe duration 308 is detected (indicating that the user's emotional statehas not changed), at the conclusion of the duration 314, there is noneed to further buffer or save the information (interchangeably referredto herein as stale data or stale information) for that duration 314.

Accordingly, embodiments of the ESM 102 are configured to receive aspecification that defines a duration 316 that, in the event nosignificant activity of the brain wave lines 304 indicates a potentialoccurrence and/or onset of a change in the user's emotional state, thestale information for that duration 310 is overwritten with newer data,is erased, is deleted, or is otherwise discarded. In an exampleembodiment, the duration 316 is predefined based on a sum of the amountof time that is needed to reliably identify the onset of a change in theuser's emotional state based on analysis of the activity of the brainwave lines 304 occurring during the duration 308. A margin of time maybe added when defining the duration 316 to ensure that relevantinformation is not inadvertently overwritten, erased, deleted ordiscarded from the information buffer 206.

In an alternative embodiment, if no significant activity is detected inthe brain wave lines 304 that indicates a potential occurrence and/oronset of a change in the user's emotional state, then the stale datacorresponding to the end of the duration 308 (or data that has a timeshortly after the end for the duration 310 by some predefined duration)is overwritten, is erased, is deleted or is otherwise discarded. Theoverwriting, erasing, deleting or discarding of old stale data may occuras new data is received from the ESM 102. For example, as a bit of newdata is received from the ESM 102, the oldest corresponding bit of datamay be overwritten, erased, deleted or discarded from the informationbuffer 206.

FIG. 3 also conceptually illustrates a stream of image information 318captured by an image capture device 110 and a corresponding stream ofaudio information 320 acquired by a microphone 112 of the ESM 102. Oneskilled in the art appreciates that the illustrated streams ofinformation are time-wise synchronized with each other and with thestreams of the EEG information 302 having a plurality of brain wavelines 304 as described herein.

In response to determining the occurrence (onset) of a change in theuser's emotional state (at the start of the duration 308), and theresultant determination of the start time and end time of the duration314, embodiments of the user content preference identification system100 pick out or otherwise access the portions of the streaminginformation associated with the duration 314. The accessed informationis then saved for detailed analysis. The detailed analysis of theinformation acquired from the EEG sensor 108, the image capturedevice(s) 110, the microphone(s) 112, and/or the eye orientation sensor210 (and the associated time, such as provided from the clock 212)during the duration 314 enables the user content preferenceidentification system 100 to identify the cause (interchangeablyreferred to herein as the life event) that precipitated the change inthe user's emotional state (as evidenced by the increased activity ofthe brain wave lines 304 during the duration 308).

Presumably, the life event which initiated the change in the user'semotional state occurred somewhere during the duration 314, and moreparticularly, during the duration 312. If the life event, at least inpart, was the user viewing a particular object, then an image of theobject will likely be included somewhere in the stream of imageinformation 322 captured by at least one of the image capture devices110 of the ESM 102. Alternatively, or additionally, any sounds heard bythe user that may have initiated the change in the user's emotionalstate will have been recorded in the audio stream 324. In somesituations, both objects seen by the user and sounds heard by the usermay have precipitated the change in the user's emotional state.Accordingly, such objects and sounds may be identified from theinformation saved during the duration 314.

Summarizing, the information acquisition process associated with achange in the user's emotion state begins with the detection of an onsetor occurrence of a change in activity levels of the brain wave lines 304acquired by the EEG sensors 108. Then, the duration 314 is defined (asthe sum of the duration 308 and the predefined duration 312). Next, theportions of the buffered or stored streams of information acquired bythe EEG sensor 108, the image capture device(s) 110, the microphone(s)112, and/or the eye orientation sensor 210 during the duration 312 areaccessed and then saved for detailed analysis. The detailed analysiswill result in the identification of viewed objects or heard sounds thatlikely initiated the change in the user's emotional state.

To conceptually illustrate how the user content preferenceidentification system 100 may identify “why” the user's emotional statehas changed (based on the identification of viewed objects or heardsounds that likely initiated the change in the user's emotional state),consider the hypothetical situation where the user's childhood friendhas grown to become a notoriously well know and famous football player.One skilled in the art appreciates that when the user watches theirfriend make a game score, whether while watching their friend in personduring a live game (referred to herein as a real life event or real lifeexperience) or while watching their friend in a televised game (referredto herein as a content life event or a content life experience), theuser will most likely feel a degree of increased emotional joy and/orsatisfaction when their friend scores during the game. Here, thisincreased emotion of joy and/or satisfaction will be detectable from ananalysis of the brain wave lines 304 acquired while the user is watchingtheir friend's performance during the game.

At this juncture in the process performed by the user content preferenceidentification system 100, it is assumed that there is no priorknowledge that the individual (here, the football player) is a closepersonal friend of the user. Embodiments of the user content preferenceidentification system 100 will learn about the user's friend, will learnthat the user experiences a higher degree of joy and satisfaction (useremotions) when watching their friend perform in a game, and will thenconstruct an emotional statement with searchable keywords that includethe identity of the friend. Using the searchable keywords in theemotional statement identifying the friend, embodiments will then searchmedia content events to identify games where their friend may be seen,and then recommend the identified media content events to the user.

For example, once the identity of the friend is known, the friend may bea player in a televised college football game. Here, the emotionalstatement will include searchable keywords that include the friend'sname and/or the team name that the friend is a member of Legacy priorart content recommendation systems based on user's viewing history wouldnot be able to recommend the televised college game to the user becausethere will be no learned knowledge about the user's emotionalexperiences (such as learning that the user enjoys watching their friendperform in a game). Later, the player may become a professional footballplayer. Embodiments of the user content preference identification system100 will be able to identify televised games (based on the team namesand/or player rosters for the named teams) where the user's friend is aplayer, and recommend the televised game to the user.

At some point, the user's friend may be a participant in and/or be thetopic of a segment of a news cast program or a documentary program.Embodiments of the user content preference identification system 100will be able to identify such news cast programs or documentary programswhere the user's friend is a subject and/or participant (based onsummary information describing topics and/or participants in the newscast programs or documentary programs), and recommend these mediacontent events to the user.

As yet another example, the friend of the user may become an actor in amovie. Embodiments of the user content preference identification system100 will be able to identify such a movie (based on summary informationabout the movie that includes the names of the actors in the movie)where the user's friend is an actor, and then recommend the movie to theuser. Legacy prior art content recommendation systems based on userpreferences determined from historical viewing patterns of the userwould never be able to recommend such content to the user because therewill be no learned knowledge about “why” the user may want to consumethat content (because the experience an increased level of joy watchingtheir friend).

Returning to FIG. 3, the stream of image information 322 is conceptuallyillustrated as a series of serially sequenced video image frames 326.Each video image frame 326 has image data or information that is used torender and present a particular image of the video captured by the imagecapture device 110. The video image frames 326 are serially presentableso as to create a moving picture (video).

To identify an object that may be associated with the change in theuser's emotional state, interchangeably referred to herein as acandidate object, image frames 326 of the stream of image information322 over the duration 314 are selected, picked or are other accessed sothat the image data of the selected frame is analyzed to identify imagesof objects included in that selected image frame 328. Preferably, animage frame 328 that resides within the duration 312 is picked foranalysis. The selected image frame 328 is analyzed using any suitableobject recognition process or algorithm now known or later developed toidentify objects shown in the selected image frame 328.

One skilled in the art appreciates that it is highly likely that aplurality of different objects will be identified from a selected imageframe 328. Some of the identified objects will be candidate objects thatmay have caused the change in the user's emotional state. Otheridentified objects will likely not be associated with the change in theuser's emotional state. Embodiments of the user content preferenceidentification system 100 are configured to identify particular objectsand their associated characteristics. Some of the identified objects maybe known to potentially be the cause of the change in the user'semotional state. These particular objects may then be designated ascandidate objects. Other identified objects may be known to not cause achange in the user's emotional state, and may then be disregarded forfurther analysis as to determining the actual source of the change inthe user's emotional state.

Images of each identified candidate object, referred to herein ascandidate object images, are then saved. Thus, each candidate objectimage is a smaller portion of the analyzed image frame. As a pluralityof image frames 326 are selected and any physical objects in those imageframes are identified, many of the identified objects from a series ofselected image frames 326 will be of the same object. Other objects maybe identified in only one of the image frames 326, or in a relativelyfew number of the image frames 326. One skilled in the art appreciatesthat since the orientation of the image capture device 110 that acquiredthe stream of image information 322 corresponds to the viewing directionof the user, that when a large number of image frames 326 each containan image of a particular object (or plurality of identified objects),then it is highly likely that the user's attention was direct towardsthat particular object (or plurality of identified objects).

In view that multiple candidate objects may be identified from the imageframes 326, the object images of the identified particular candidateobject (or plurality of identified candidate objects) are saved forlater presentation to the user. One or more representative candidateobject images will be selected for presentation. The user will then beasked to identify which of the candidate objects were the source oftheir recollected change in emotional state. Further, the user may beasked to describe their changed emotional state. Alternatively, oradditionally, the user may be presented the image frames 326 (as stillimages and/or as a video) and then asked to identify the objects thatcaused a change in their emotional state.

Returning to the hypothetical example of the user's personal closefriend who is a football player, one skilled in the art understands thatthe stream of image information 322 was captured while the user waswatching their friend playing in the game. Since the stream of imageinformation was acquired by the image capture device 110 of the ESM 102,it is understood that the user would have been watching a live game or atelevised game (a media content event). Regardless of what the user wasviewing (the live game or the televised game), an image of their friendwill be included in many of the image frames 326 that are within theduration 314.

For example, the video image frame 328 is selected and is used togenerate the image that includes the image of the football player 330who is the friend of the user. Here, a portion 332 (an area of space) ofthe image frame 328 has an image of the football player 330. The imagedata from the portion 332 is selected and an object image 334 thatincludes the football player 330 is generated there from, and is thensaved as a candidate object image 332 by embodiments of the user contentpreference identification system 100.

At this juncture, one skilled in the art appreciates that the usercontent preference identification system 100 has not yet identified anyparticular identifiable objects as being the source of the change in theuser's emotional state. Further, it is highly likely that a plurality ofother object images will be generated of other identifiable objects thatare visible in the analyzed image frames 326. For example, otherplayers, referees, and/or bystanders may be identified. Structuralobjects, such a bleachers or goals, may be identified. Particularactions may also be identified from a series of analyzed image frames326, such a game score or other important activity. However, at thisjuncture, embodiments of the user content preference identificationsystem 100 require additional information to determine which of theparticular identified objects are associated with the actual source thatinitiated the change in the user's emotional state.

In some embodiments, the information acquired from the eye orientationsensor 210 may facilitate identification of candidate objects that arelikely sources of the change in the user's emotional state. Theinformation about the orientation of the user's eyes may be used todefine a particular region in the analyzed image frames 328 that theuser's attention was directed towards. That is, the eye orientationsensor 210 may be used to identify a particular relevant area of ananalyzed image frame 328. Objects that are identified which are outsideof the identified area of the user's viewing direction may bedisregarded as being candidate objects. Objects that are identifiedwhich are within the identified area of the user's viewing direction maybe designated as being candidate objects

Additionally, or alternatively, sounds in the audio information acquiredby the microphone 112 is similarly analyzed to identify one or moresounds that were heard by the user. The identified sounds may also bethe source of, or part of the source of, the change in the user'semotional state. Audio clips 336 containing the candidate sound aregenerated from the audio stream 324 acquired during the duration 314 andare saved as candidate audio sounds. However, at this juncture,embodiments of the user content preference identification system 100require additional information to determine which of the particularidentified sounds are associated with the actual source that initiatedthe change in the user's emotional state.

Further analysis of the brain wave lines 304 acquired by the EEG sensor108 allow embodiments of the user content preference identificationsystem 100 to identify particular emotional states of the user. Moreparticularly, analysis of the frequency and phases of the neuraloscillations of the plurality of brain wave lines 304 can provide anindex of the dynamic interaction between brain regions involved inemotion perception. Any suitable methodology of analyzing EEG acquiredinformation now known or later developed may be used by the variousembodiments of the user content preference identification system 100 toidentify particular emotions of the user.

In example embodiments, eight different emotions are identified from theacquired EEG information 302. The eight emotional states areanticipation, surprise, joy, sadness, disgust, trust, anger and fear.Further, the change in the user's emotional state may be viewed in termsof a range of emotions. Ranges of emotion include anticipation vs.surprise, joy vs. sadness, disgust vs. trust, and anger vs. fear.Although identification of other emotions is possible, these eightemotions are particularly useful is ultimately determining the user'semotional preferences, dislikes, and/or disinterests for content.

Anticipation is defined as an emotional feeling of excitement about someevent that is going to happen, or is likely to happen, in the nearfuture. Surprise is defined as an emotional feeling of wonder,astonishment, or amazement, as a result of experiencing an event thatwas unanticipated or that occurred unexpectedly. Joy is defined as anemotional feeling of emotion evoked by well-being, success, goodfortune, or by the prospect of possessing what one desires. Sadness isdefined as an emotional feeling characterized by feelings ofdisadvantage, loss, despair, grief, helplessness, disappointment andsorrow. Disgust is defined as an emotional feeling of revulsion orprofound disapproval aroused by something unpleasant or offensive. Trustis defined as an emotional feeling that someone is good and honest andwill not harm you, or that someone or something may be relied upon.Anger is defined as an emotional feeling characterized by a strongfeeling of annoyance, displeasure, or hostility. Fear is defined as anemotional feeling of an unpleasant anticipation or awareness of danger,pain, and/or harm. Other embodiments may use fewer than the eightidentified emotions, more than the eight identified emotions, and/ordifferent emotions.

As time progresses, for a particular user, embodiments of the usercontent preference identification system 100 generate an emotionaldatabase that includes the acquired identified emotion events (where theemotional event is associated with one of the eight emotions:anticipation, surprise, joy, sadness, disgust, trust, anger and fear),identified candidate objects (and information to access stored candidateobject images) and identified candidate sounds that may be the source ofthe change in the user's emotional state, and whether the acquiredchange in the user's emotional state occurred as a result of the userexperiencing a real life event (interchangeably referred to herein as areal life experience), or, was the result of the user viewing aparticular media content event (referred to herein as a content lifeexperience or content life event). Further, magnitude or valueinformation may be saved for each emotional event that is indicative ofthe degree of emotion that the user experience during the emotionalevent (as determined from the magnitude of change in the acquired brainwave lines 304). In an example embodiment, the emotional database may bevisually presented to an observer using a matrix format (referred toherein as an emotion matrix).

For each emotional event, the information will include any associatedemotions of anticipation, surprise, joy, sadness, disgust, trust, angerand/or fear. For each emotional event, at least one candidate object(and more likely a plurality of candidate objects) and/or a candidatesound (or a plurality of candidate sounds) will be associated with eachemotional event. After a sufficient number of emotional events have beenaccumulated, embodiments may learn which objects and/or sounds areassociated with particular emotions. That is, embodiments of the usercontent preference identification system 100 are able to correlateviewed objects and/or heard sounds with particular changes in emotionalstates.

Returning to the hypothetical example of the user's friend who hasbecome a notorious football player, it is likely that over time theemotional database for the user will have a plurality of emotionalevents pertaining to the user's friend. Some life events, such as theirfriend scoring a game point or performing particularly well during aparticular game play, may elicit an increase in the emotions of joy,anticipation, and/or surprise. Alternatively, if there is an accidentthat involves their friend, the user may experience an increase inanticipation, surprise, sadness, fear, and/or anger. Regardless of thechange in emotional state of the user during the game, or over a seriesof games performed over time, embodiments of the user content preferenceidentification system 100 will “learn” that the user's friend isassociated with a change in the user's emotional state.

As noted herein, embodiments of the user content preferenceidentification system 100 interact with the user at some point(s) intime to obtain user feedback regarding their particular experiencedemotional states and to obtain an explanation of “why” the experiencedtheir emotions. Embodiments will query the user about particular lifeevents, ask them to recall the experience, identify their emotions thatthey were feeling during the life event, and then identify the viewedobjects and/or heard sounds that precipitated their change in emotionalstate.

Returning to the hypothetical example of the user's friend who is afootball player, embodiments of the user content preferenceidentification system 100 will present to the user the candidate imageobjects identified from the captured images acquired by the imagecapture devices(s) 110, and/or present sounds acquired by themicrophone(s) 112. The user will be asked to recall their emotionalexperience during the life event, and then identify one or morecandidate objects and/or sounds that were the cause of the change intheir emotional state. Here, the user would identify their friend shownin the candidate object images. Further, the user may be asked toidentify the pertinent candidate object. Here, the user may say orprovide suitable input that identifies the name of their friend.

Other candidate objects not associated with the change in the user'semotional state will be identified by the user as not being relevant tothe change in their emotional state. These candidate objects can then beknown to be objects that will not likely elicit an emotional change inthe user.

Similarly, sounds may or may not precipitate and/or contribute to thechange in the user's emotional state. In such cases, embodiments of theuser content preference identification system 100 “learn” that somesounds are not likely to elicit an emotional response from the user. Onthe other hand, the recorded sounds presented to the user may cause theuser to indicate that these sounds are associated with their change inemotions. For example, the playing of the user's national anthem or teamsong during the game may cause the user to experience the emotion of joyand/or satisfaction. The user may indicates such in response to a queryfrom the user content preference identification system 100, and then theuser content preference identification system 100 would “learn” thatthis particular music will likely elicit an emotional response from theuser.

Alternatively, the user may have experienced no particular emotionalchange because of the playing of the national anthem and/or team song.Such indifference may be indicated by the user. (Rather, the user mayhave experienced an emotion caused by viewing their friend who was,coincidentally, viewed while the national anthem and/or team song wasbeing played.) Thus, embodiments of the user content preferenceidentification system 100 would “learn” that the user is likelyindifferent to the playing of this particular music.

Once embodiments of the user content preference identification system100 have identified a particular object and/or sound that is likely toelicit an emotion from the user, an emotional statement is defined. Theemotional statement is a textual phrase that identifies the objectand/or sound with particularity. That is, the emotional statementincludes a textual description of the identified object(s) and/orsound(s) The emotional statement is associated with one or more emotionsand/or may optionally include a textual characterization or descriptionof the emotional state of the user. The emotional statement, in someembodiments, is referred to as a “whyse” statement. The term “whyse” isa combination of the two terms “why” and “wise” that indicates that theemotional statement is learned in an intelligent or wise manner thatrelates to why a user is likely to have an emotional response to aparticular object and/or sound.

FIG. 4 is a block diagram of an example user content preferenceidentification device 106. The example user content preferenceidentification device 106 comprises one or more processor systems 402, amemory 404, a transceiver/connector 406, an optional information buffer408, and a user emotional database 410.

The memory 404 may be any suitable persistent memory medium or memorystorage device that comprises regions for storing various logic modules.The logic modules, when executed by the processor system 402, performthe various functions and operations of the user content preferenceidentification device 106. The logic modules include the emotional statemonitor (ESM) information receiving logic 412, the emotional statechange determination logic 414, the image frame selection logic 416, theobject identification logic 418, the user query logic 420, the emotionalstatement generation logic 422, the content identification logic 424,and the content recommendation logic 426. Other logic modules (notdescribed) may also reside in memory 404. The logic modules 412-426 areillustrated and described as separate logic modules in an exampleembodiment. However, the logic modules 412-426 may be integrated witheach other, and/or may be integrated other logic modules that performother functions. Further, one or more of the logic modules 412-426 mayreside in separate memory mediums. Additionally, one or more of thelogic modules 412-426 may be concurrently executed by multiple processorsystems 402.

The user emotional database 410 is a persistent memory medium thatstores various information about each user. In example embodiments, theuser emotional database 410 is implemented as a relational databaseusing portions of the memory medium that have been uniquely associatedwith each individual user. For example, the user 1 information 428-1 isassociated with a first user and the user information 428-2 isassociated with a second user. It is appreciated by one skilled in theart that information for any number of user may be stored in the useremotional database 410.

The information contents for each user, such as for the exemplary i^(th)user that has been stored in the user i information 428-i, includes theuser's emotional experiences matrix 430, the user's emotional statements432, recommended content 434, and a user identifier 436. The identifier436 is any suitable identifier that uniquely identifies the user, suchas a name, and address, an account number, or other suitable uniquepersonal identifier.

The emotional experiences matrix 430 stores information for each lifeexperience that is identified from the information provided by the ESM102 being worn by the identified user. After a sufficient amount of timeof monitoring a particular user, user information from a large number oflife experiences for that particular user will be accumulated and willbe stored in the emotional experiences matrix 430 for that user.

For each life experience for the identified user, the user's emotionalexperiences matrix 430 stores information identifying the particularemotion experienced by the user. The identified emotion (for example,but not limited to, anticipation, surprise, joy, sadness, disgust,trust, anger, and/or fear) is stored in the emotion 438 portion of theemotional experiences matrix 430. As noted herein, the user's particularemotion may be determined from an analysis of the user's brain waves 304(FIG. 3) acquired from the ESM 102 (FIG. 1).

The RL/Content experience 440 is information that identifies whether thelife experience occurred in real life (RL) or occurred while viewing(consuming) a media content event (denoted as a content life experienceor a content life event). These emotional change events or experiencesare generically referred to herein as life events or life experiences,respectively.

One or more object images 334 are generated from the analysis of theimage information acquired by the image capture device(s) 110 of the ESM102 for a particular real life event (a sub-type of a life event). Asnoted herein, the object images 334 are generated in response todetermining that there has been a potential occurrence and/or onset of achange in the user's emotional state based on the analysis of the brainwave lines 304 during the duration 308. Generated object images 334 arestored in the user's emotional experiences matrix 430. Further, one ormore audio clips 336 acquired by the microphone(s) 112 may be stored inthe user's emotional experiences matrix 430 for the same real lifeevent.

In some embodiments, the user emotional database 410 may employ aplurality of different memory mediums that store the user informationfor the plurality of different users. Such multiple memory mediums maybe located locally at the user content preference identification device106. Alternatively, or additionally, the multiple memory mediums may bedistributed remotely from the user content preference identificationdevice 106. In some embodiments, one or more remotely located memorymediums that store the user information of the user emotional database410 may be configured to be communicatively coupled with a plurality ofdifferent user content preference identification devices 106. A workingenvironment having the implemented user content preferenceidentification system 100 is anticipated to have thousands, or evenhundreds of thousands, of different users. Accordingly, a distributedemotional database 410 system and a plurality of user content preferenceidentification devices 106 working in concert together would facilitatethe processing of life event information received from a very largenumber of, or even an unlimited number of, different users.

The transceiver/connector 406 of the user content preferenceidentification system 100 is a communication structure thatcommunicatively couples the user content preference identificationdevice 106 to the communication network 116. The transceiver/connector406 may be configured to receive and transmit wireless communicationsvia a wireless link established to the communication network 116.Alternatively, or additionally, the transceiver/connector 406 may employa wire-based connection to become communicatively coupled to thecommunication network 116. Once the user content preferenceidentification device 106 is communicatively coupled to thecommunication network, communication links can be established to aplurality of portals 104 that are receiving information acquired by oneor more ESMs 102.

Embodiments may be provisioned with the optional information buffer 408.The information buffer 408 may operate similar to the information buffer206 implemented in the ESM 102. Accordingly, a plurality of ESM(s) 102that communicate on a real time basis, or on a near real time basis, theinformation acquired from the EEG sensor 108, the image capturedevice(s) 110, the microphone(s) 112, and/or the eye orientation sensor210 (and the associated time, such as provided from the clock 212) isbuffered into the information buffer 408. The processor system 402,executing the emotional state change determination logic 414, wouldmonitor the received information on a real time basis, on a near realtime basis, and/or at a later time, to identify the onset of anemotional state change in the user. Then, the information from the EEGsensor 108, the image capture device(s) 110, the microphone(s) 112,and/or the eye orientation sensor 210 (and the associated time, such asprovided from the clock 212) for the duration 314 can be picked from theinformation buffer 408 for further processing.

The information buffer 408 may be a relatively large capacity typebuffer memory device, and/or may be comprised of multiple buffer memorydevice units, to accommodate the information concurrently received froma relatively large number of different ESMs 102. In such operatingenvironments, the information received from a particular ESM 102includes identifying information that identifies that ESM 102 and/or theuser who is wearing the ESM 102. Accordingly, the received informationcan ultimately be associated with a particular user.

In embodiments where the determination of an emotional state change isdetermined at an ESM 102 such that only the information acquired by theEEG sensor 108, the image capture device(s) 110, the microphone(s) 112,and/or the eye orientation sensor 210 (and the associated time, such asprovided from the clock 212) during the duration 314 is communicated tothe user content preference identification device 106, the informationbuffer 408 may be used to temporarily store the received information.Accordingly, the information may be retrieved from the informationbuffer 408 and be processed to add the information into that user'semotional experiences matrix 430.

The processor system 402, executing the ESM information receiving logic412, processes the incoming information as it is being received from theplurality of ESMs 102. Accordingly, the processor system 402, executingthe ESM information receiving logic 412, manages operation of thetransceiver/connector 406 to manage communications to and from thecommunication network 116, operates to store received information intothe information buffer 408, and then operates to access the storedinformation for further processing.

It is appreciated by one skilled in the art that the processor system402 may be any suitable processor-based system or device. Further, someembodiments of the user content preference identification device 106 mayemploy multiple processor systems 402. The use of multiple processorsystems would facilitate concurrent processing of information receivedfrom a plurality of different ESMs 102.

The processor system 402, executing the image frame selection logic 416,processes the image information for the duration 314 by selecting one ormore image frames 326 (FIG. 3). Each selected image frame 326 isanalyzed by the processor system 402 (executing the objectidentification logic 416) to identify one or more physical objects shownin the selected image frame 326. Depending upon the embodiment, theimage frames 326 may be selected on a periodic basis over the duration314. For example, every tenth image frame 326 (that is, image framesthat are separated by nine intervening image frames 326) may be selectedfor analysis. Any suitable predefined number of intervening image framesmay be used in the various embodiments.

Alternatively, image frames separated by a predefined separationduration may be selected. An example separation duration may be everytwo seconds. Any suitable predefined separation duration may be used inthe various embodiments.

Some embodiments may be configured to use a first number of interveningframes or a first separation duration to initially identify one or moreparticular objects that are shown in each of the selected image frames326. A single identifiable object(s) may be identified by the objectrecognition analysis of the selected image frames 326. For example, asingle predominate object may be initially identified in the initiallyselected first plurality of image frames 326 that are analyzed inaccordance with the object identification logic 416. The user contentpreference identification system 100 may then conclude with reasonablecertainty that the identified object is most likely the candidate object(that precipitated the change in the user's emotional state). In suchsituations, additional image frames 302 may not need to be analyzed.

However, if no particular object(s) is identifiable in the analyzedfirst plurality of image frames 326, then more analysis may be requiredto identify any particular object(s) that is the likely source of theuser's change in their emotional state. Accordingly, then an additionalsecond plurality of intervening image frames 302 may be picked from theduration 314 for further analysis (based on a smaller number ofintervening frames or based on a shorter second separation duration).

Conversely, a plurality of different objects may be initially identifiedin the selected first plurality of image frames 326. And, each imageframe 326 of the first plurality may show different objects.Accordingly, the user content preference identification system 100 maynot be able to identify candidate object with any degree of reliabilityor certainty. Accordingly, analysis of additional image frames 326 willbe required to identify one or more candidate objects that may haveprecipitated the user's emotional state change. The additional secondplurality of image frames 326 can then be selected and analyzed toidentify the physical objects shown in the image frames 326.

Once candidate objects have been identified from the selected analyzedimage frames 326, some embodiments are configured to generate objectimages 334 that are saved into the object images 334 portion of theemotional experiences matrix 430. Each object image (such as theexemplary object image 334) show the identified candidate object.

Alternatively, or additionally, a descriptor of the identified candidateobject may be generated and saved (that includes a life event keyword).For example, a particular type of dog may be identified as a candidateobject by the object identification logic 418. An image 334 of the dogand/or a descriptor identifying the type of dog may be saved into theobject images 334. If multiple candidate objects are identified, thenthe multiple representative object images 334 (and any descriptors) aregenerated and then saved into the object images 334 portion of theemotional experiences matrix 430. Alternatively, the entirety of theimage frame 326 that have the one or more identified candidate objectsmay be saved.

Object recognition algorithms are well known in the arts. Such objectrecognition algorithms, now known or later developed, may be used byembodiments of the user content preference identification system 100 toidentify one or more candidate objects from selected image frames 326.Further, algorithms now known or later developed for selecting a portionof an image frame 326 having an identifiable object may be used togenerate the object images 334.

When a plurality of image frames 326 are analyzed, and when the sameobject is identified in each image frame 326 (though the identifiedobject likely is at a different portion or location in each analyzedimage frame 326), the generated plurality of image objects 324 will bethe same, substantially the same, or similar to each other. Accordingly,some embodiments are configured to save a single representativecandidate object image 334 of the identified candidate object, oralternatively a limited number of candidate object images 334, into theemotional experiences matrix 430. Accordingly, embodiments of the usercontent preference identification system 100 may be configured to selecta representative one of the generated object images 334 as a candidateobject image 334. Alternatively, a selected number of the generatedobject images 334 may be saved into the user emotional database 410 soas to better represent the identified object. For example, a sufficientnumber of image objects (of the same physical object) may be generatedand then stitched together to emulate a video clip of the object thatthe user saw during the associated life event.

The audio information is optionally analyzed during the duration 314 toidentify sounds that may have, in whole or in part, precipitated theonset of the user's change in emotional state. If a candidate sound isidentified, an audio clip 336 having the identified sound is generatedand is stored in the audio clips 336 portion of the emotionalexperiences matrix 430. Candidate sounds may include songs, music,and/or other noise that is perceptible by the user.

Embodiments of the user content preference identification system 100also ascertain if the user experienced a real life event or if the userwas viewing a media content event during their change in emotionalstate. A flag, bit, or the like may be defined and stored into theRL/Content experience 440 portion of the emotional experiences matrix430 to indicate a that the user's change in emotional state occurredduring a real life event or a content event.

When the user is viewing and/or listening to a media content event, theimage capture device(s) 110 and/or the microphone(s) 112 of the ESM 102,respectively, acquire image and sound information from the user'sperspective. That is, the view of the content being seen by the user andthe sounds of the audio track of the content being heard by the user areacquired.

One skilled in the art appreciates that if the life event isprecipitated by consuming a media content event, that the particularmedia content event can be identified in a variety of manners. Once theparticular media content event being consumed during the content lifeevent is identified, then a wealth of information about that particularmedia content event is available that may be further analyzed toidentify possible causes of the user's detected change in emotionalstate that was experienced while consuming that particular media contentevent.

Because the time that the user was consuming the media content event isknown or is determinable based on time information from the ESM 102,embodiments of the user content preference identification device 106 maybe optionally configured to identify the particular media content eventthat was being consumed by the user during that life experience. In anexample embodiment, the user content preference identification device106 accesses time of broadcast information (that may be available froman electronic program guide or the like) that corresponds to the time ofthe acquired information received from the ESM 102. Embodiments thenidentify available media content events that the user might have beenconsuming during the onset of the detected change in emotional stateduring the duration 314. Then, image and/or sound recognition logic maybe able to identify the physical objects being seen and/or sounds heardby the user, and then compare the identified object and/or sound withimages and/or sounds contained in a particular media content event.

For example, a particular song that has been identified in the soundbeing heard by the user (as acquired by the microphone(s) 112) may beincluded in the sound track of a media content event. Since informationidentifying the music and/or songs of the sound tracks used in aparticular movie (which may be identified in meta data of the mediacontent event and/or that may be stored at another remote site thatstores information pertaining to media content events) is available tocompare with the music and/or songs being heard by the user, theparticular media content event being consumed by the user during thecontent life event may be identified.

Alternatively, or additionally, image analysis logic may identify animage(s) of one or more actors (physical objects) being viewed by theuser (as acquired by the image capture device(s) 110). Then, facialrecognition logic may process the image information to identifyparticular actors being viewed by the user. Information identifying theactors in a particular movie (which may be identified in meta data or atanother remote site that stores information pertaining to media contentevents) is accessed by the user content preference identification device106 to compare with the identified actors being seen by the user. Whenthe identified actors seen by the user correspond to the actors of oneof the plurality of media content events that are available forconsumption by the user, then that particular media content event withthe corresponding actors can be determined to be the media content eventthat was being consumed by the user during the content life event.

Alternatively, or additionally, the image information acquired by theimage capture device(s) 110 may present image information in thevicinity of a display that the user is viewing the media content eventon. For example, a digital indicator disposed on the surface of the acomponent of the presentation system 120 and/or the media device 118 mayvisually indicate the current channel that is being received by themedia device 118 that the user is operating to present the media contentevent. Thus, identification of the visual digital display, andsubsequent identification of the channel information, may be done by theuser content preference identification device 106 based on analysis ofimage information acquired by the ESM 102. The channel information thenis correlated with the information available from an electronic programguide or the like to identify the particular media content event beingconsumed by the user at the time of the content life event (since thechannel identifier indicates that channel of broadcasting content).

Alternatively, or additionally, the media device 118 may be incommunication with the ESM 102 and/or the portal 104. The media device118 may be optionally configured to communicate identificationinformation that identifies the currently presenting media content eventand/or the currently received channel. For example the media device 118may emit a wireless IR signal, a wirelesses RF signal, a Bluetoothsignal or the like that is detectable by the ESM 102 and/or the portal104. Then, the information identifying the media content event and/orthe current channel can be provided to the user content preferenceidentification device 106 for determination of the media content eventbeing consumed by the user at the time of the potential occurrenceand/or onset of a change in the user's emotional state.

Once the particular media content event has been identified, embodimentsof the user content preference identification device 106 may access avariety of information pertaining to the identified media content event.For example, textual information describing the subject and/or theme ofthe identified media content event and/or a story line may be accessed(typically from a remote site that stores information pertaining tomedia content events). Actors of the identified media content event maybe determined (potentially identifying actors that the user likes,dislikes, and/or is neutral about). Set location information may beacquired (potentially identifying locations that the user likes,dislikes, and/or is neutral about).

Based on time information provided by the ESM 102, individual scenes maybe optionally identified. Then, scene information describing attributesof a particular scene may be obtained. For example, actors in that scenemay be determined (potentially identifying actors that the user likes,dislikes, and/or is neutral about). Dialogue of that particular scenemay be acquired (potentially identifying conversational topics that theuser likes, dislikes, and/or is neutral about). Scene props (objectsused to facilitate the filming of the media content event) may beidentified (potentially identifying objects that the user likes,dislikes, and/or is neutral about). Scene sound track information mayidentify the songs and/or music being presented during that scene(potentially identifying songs or music that the user likes, dislikes,and/or is neutral about).

Summarizing, for each identified emotional event, embodiments of theuser content preference identification system 100 identify theparticular emotion(s) that the user experienced (stored in the emotion438 portion of the user's emotional experiences matrix 430), identifiesone or more candidate objects that may have precipitated the change inthe user's emotional state (wherein object images and/or descriptors ofthe physical object are stored in the object images 334 portion of theuser's emotional experiences matrix 430), identifies one or more soundsthat that may have precipitated the change in the user's emotional state(stored in the audio clips 336 portion of the user's emotionalexperiences matrix 430), and determines if the user was experiencing areal life event or was viewing a media content event (stored in theRL/content experience 440 portion of the user's emotional experiencesmatrix 430). Accordingly, a record for each particular identifiedemotional life event can be generated and saved into the user emotionaldatabase 410. The database record would specify the emotion, include oneor more candidate object images, optionally include one or more audioclips, and include a specification of the type of life event (a reallife event or a viewing content event).

At this juncture, one skilled in the art appreciates that an additionallevel of analysis is required of the information stored in the user'semotional experiences matrix 430 before emotional statements can bedetermined. For example, for a particular life event, the object images334 may include a plurality of object images for different identifiedphysical objects seen in the analyzed image frames 326. Further, anyidentified sounds stored in the audio clips 336 may, or may not be,involved with the user's change in emotional state. There is no good wayto automatically determine which of the particular objects, and/orwhether any of the sounds heard by the user, are the source of theuser's change in emotional state that occurred during the life event.

Accordingly, embodiments of the user content preference identificationsystem 100 are configured to query the user about their life experience.An exemplary embodiment of the user content preference identificationsystem 100, executing the user query logic 420, may query the user byfirst describing to the user one or more characteristics and/orattributes pertaining to the detected life event and the determinedemotional state of the user (the determined user's emotion).

For example, the user may be shown the candidate object images generatedduring the duration 314. Candidate objects may be presented as still orvideo images on the media presentation system 120 and/or the mediadevice 118 having a display. Alternatively, or additionally, candidateobject images may be presented to the user via a suitable augmentedreality device, such as the ESM 102 that resembles a pair of glassesthat are worn on the head of the user. Another example may be ahelmet-like device that encloses the user's head, such as a virtualreality head set, a head mounted display, or the like.

Sounds heard by the user at the time of the determined life event may beplayed back to the user. Sounds may be presented by the mediapresentation system 120 and/or the media device 118 having speakers orearphones. Alternatively, or additionally, candidate object images maybe presented to the user via a suitable augmented reality device, suchas the ESM 102 that resembles a pair of glasses that are worn on thehead of the user. Another example may be a helmet-like device thatencloses the user's head, such as a virtual reality head set, a headmounted display, or the like.

Other information may also be provided to the user. For example, if theuser was consuming a media content event, information identifying theparticular media content event and/or particular scene may be indicatedto the user. The scene of the media content event that was beingpresented at the time of the potential occurrence and/or onset of achange in the user's emotional state may be optionally presented to theuser.

The user, after contemplating the presented information, after viewingthe acquired images and/or after hearing the acquired the acquiredsounds, will be asked to identify any of the presented candidate objectsthat may have caused (precipitated) their emotional state change. Theuser may also be asked to identify any of the candidate sounds that mayhave caused their emotional state change. Additionally, the user will beasked to confirm whether the type of emotion they experienced during thelife event is the same as the determined emotion, or whether theirexperienced emotion was different from the determined emotion (in whichcase the emotion information may be updated).

Optionally, if the user is wearing their ESM 102, acquired informationmay be analyzed while the user is being queried. For example, if aparticular object or sound being presented to the user during the queryagain causes a change in the user's emotional state (as indicated by anincrease in the acquired brain wave lines 304), then confirmation of theuser's likely response to similar images and/or sound may be learned byembodiments of the user content preference identification system 100.

Further, when the user is being presented a plurality of candidateobjects during a query, then the information acquired by the eyeorientation sensor 210 may be used to identify the particular one(s) ofthe candidate objects that the user's view was directed to during thequery. The user can then be presented the object(s) that they werelooking at (as determined by the acquired eye sensor information). Theuser can then view the individual candidate object images one at a time,and their emotional response can be detected (as indicated by anincrease in the activity of the acquired brain wave lines 304 duringeach presented identified sound).

Alternatively, the plurality of candidate objects may be presented oneat a time in a serial fashion (using a suitable predefined delay), andthe brain wave lines 304 may be analyzed to determine if the user ishaving an emotional response to a particular presented candidate objectimage. In one embodiment, rather than using a predefined duration forcandidate object image presentation, the user's brain wave lines 304 canbe monitored for an increased activity. If no increased activity in theacquired brain wave lines 304 is detected during presentation of aparticular candidate object image, then the presented candidate image isnot one that elicits an emotional response from the user. On the otherhand, if an increased activity in the acquired brain wave lines 304 isdetected during presentation of a particular candidate object image,then the presented candidate image can be identified as one that elicitsan emotional response from the user.

In addition, or alternatively, an augmented reality avatar(interchangeably referred to herein as a “bot”) may verbally ask theuser specific questions during the query. For example, the bot may askthe user which particular candidate object(s) which caused theiremotional state change. The bot may ask the user to describe theiremotional response to view in the candidate object(s) (and/or tosounds). Natural language processing algorithms may then be used toconvert the user's spoken answer to text, and then to identify thecandidate object(s) that the user identified in response to the bot'sverbal query.

Further, if a detectable emotional change is detected when the user isbeing presented an audio clip of candidate sounds, then the audio clipmay be parsed into additional sections with specific identifiable sounds(thus increasing granularity of the audio information). The user canthen hear the individual identified sounds one at a time, and theirresponse can be detected (as indicated by an increase in the activity ofthe acquired brain wave lines 304 during each presented identifiedsound).

Summarizing, the user will be asked during the user query to specifytheir change in emotions and/or their emotional state during the lifeevent (which occurred during the life event duration). The user'sspecified emotional state is compared to the determined emotional statethat was determined from the information corresponding to the acquiredplurality of brain wave lines acquired during the life event duration314. The determined emotional state is correctly determined when thedetermined emotional state is the same as the user's specified emotionalstate. In contrast, the determined emotional state may be changed to theuser's specified emotional state when the determined emotional state isdifferent from the user's specified emotional state.

Optionally, other information and/or commentary provided by the userwill be captured as part of the user query process. For example, theuser may be asked to explain why they had a particular emotionalresponse during that life event by the bot. For example, some cultural,religious, or other societal aspect of the user's life may be related tothe particular emotional response of the user during the life event thatis the subject of the user query. The user may also provide commentaryabout past experiences. For example, the user may have had a favoritepuppy or other pet when they were young. If the identified object thatis associated with the occurrence and/or onset of the change in theuser's emotional state is a dog, and in view of the user's commentaryregarding fondness for their childhood pet, embodiments of the usercontent preference identification system 100 may conclude that the userlikes pet dogs (and accordingly, then identify media content eventsrelating to and/or having story lines pertaining to pet dogs under theassumption that the user may like such media content events).

Based on the user's responses during the user query process, thecandidate object(s) and/or candidate sound(s) that precipitated thechange in the user's emotional state are identified by the user contentpreference identification system 100 based on the user's specificationof which particular objects and/or sounds caused their emotional statechange. These objects and sounds are indicated as being relevant to theuser's change in emotional state, and are stored and are noted as beingrelevant to a user's emotion in the emotional experiences matrix 430 ofthe user emotional database 410 for that particular life event.

The other identified objects and/or sounds which were not identified bythe user as being relevant to their emotional state change can then beidentified as not being relevant to the user's emotional state change.In some embodiments, the information identifying non-relevant physicalobjects and/or sounds are stored or retained in the user's emotionalexperiences matrix 430 for that particular life event. These physicalobjects and/or sounds that the user did not indicate as being relevantto their changed emotional state may be flagged or otherwise identifiedas being physical objects and/or sounds that are of disinterest to theuser. In some embodiments, these non-relevant objects and/or sound maybe optionally deleted, erased or otherwise discarded.

In some instances, one or more of the identified objects and/or soundsmay be identified by the user as being disliked by the user. In someembodiments, the information identifying such disliked physical objectsand/or sounds are optionally stored or retained in the user's emotionalexperiences matrix 430 for that particular life event. These physicalobjects and/or sounds that the user indicated as being relevant to theirchanged emotional state may be flagged or otherwise identified as beingphysical objects and/or sounds that are disliked by the user. In someembodiments, these disliked objects and/or sound may be optionallydeleted, erased or otherwise discarded.

In some situations, the user may not respond to a specific individualquery. It may be that the user chooses not to respond because they havea great emotional reaction to the query (such as question from the bot,and/or a presented candidate object image or sound). Here, the user mayotherwise experience great discomfort, anger, fear or other negativeemotion such that they simply refuse to elaborate or articulate ananswer to the specific query. Since the user is having an emotionalresponse (as indicated by the currently acquired brain wave lines 304),embodiments of the user content preference identification system 100 maylearn that that the user is experiencing a negative type emotion, andthen conclude that particular query. That is, the user will not be askedrelated and/or follow up questions, and/or be presented relatedcandidate object images and/or sounds.

Accordingly, after receiving user feedback obtained during the userquery process, the user's emotional experiences matrix 430 will have,for a plurality of different life events, an accurate representation ofthe factors (what physical object the user saw and/or what sound theuser heard) which precipitated the change in the user's emotional state.After similar information is obtained for the user from many lifeevents, even thousands of or hundreds of thousands of live events,embodiments of the user content preference identification system 100will have sufficient information to conclude (learn) what type of lifeevents the user is likely to respond to, and be able to predict theemotional level and/or type of emotional response of the user tospecific stimuli.

Furthermore, one skilled in the art appreciates that the informationabout what viewed physical objects and sounds heard by the user that arenot relevant to the user's changed emotional state, and/or that aredisliked by the user, may also provide relevant information about theuser. For example, if a sufficient number of other life events also havesimilar, or even the same, identifiable objects and or sounds that arenot relevant to the user's changed emotional state and/or are dislikedby the user, then these objects and/or sounds may be associated with adisinterest or a dislike, respectively, on the part of the user.

For example, an identified sound may be that of an aircraft passingoverhead. Some users may not have even recalled and/or noticed that anaircraft was in their vicinity during a plurality of different real lifeevents. Thus, embodiments of the user content preference identificationsystem 100, after a sufficient number of life events that recordedsounds of passing aircraft, may conclude (learn) that the user is notreally interested in aircraft. In contrast, the user may haveconsistently become excited and/or joyful when they heard the sound ofnearby passing aircraft. Thus, embodiments may conclude (learn) that theuser has a particular like or preference for aircraft. Conversely, ifthe user became fearful each time they heard passing aircraft,embodiments may conclude (learn) that the user has a fear (dislike) ofaircraft and/or has a fear of flying in general.

Based on one or more life experiences, one or more emotional statements432 are generated and saved into the user's emotional experiences matrix430. An emotional statement is a descriptive textual phrase thatdescribes and/or characterizes the user's anticipated emotional responseto perceived emotional stimuli (viewing a physical object and/or hearinga particular sound) during a future life event. That is, the emotionalstatement describes a predicted life event that is likely to generate aparticular emotion experience(s) in the user if a similar life eventoccurs in the future. Preferably, the emotional statement describes“why” the user is likely to experience a particular emotional state.Preferably, the emotional statement identifies with particularity theobject(s) and/or sound(s) that are anticipated to cause an emotionalresponse when encountered by the user. The identification withparticularity of the object(s) and/or sound(s) may be used to definesearchable keywords that can be associated with the identified object(s)and/or sound(s).

The processor system 402, based on the information contained in theuser's emotional experiences matrix 430 and while executing theemotional statement generation logic 422, generates one or moreemotional statements. These generated emotional statements are thensaved into the emotional statements 432 portion of the user information428 of the user's emotional experiences matrix 430. For any individualuser, over time, a plurality of different emotional statements may begenerated as saved.

To generate an emotional statement, embodiments of the user contentpreference identification system 100 analyze the contents of the user'semotional experiences matrix 430 to identify a plurality of lifeexperiences that had the same or similar emotional response in the userthat were caused by the same or similar candidate objects and/orcandidate sounds (as verified by the user during the user queryprocess). Based on the plurality of identified common life experiences(that elicited in the user the same or similar emotions and that werecaused by the same or similar viewed physical objects and/or heardsounds), embodiments of the user content preference identificationsystem 100 determine and generate the emotional statement for the user.That is, embodiments conclude (learn) that a particular object viewed bythe user at a future time, and/or that a particular sound heard by theuser at a future time, can be expected to elicit a particular emotionalresponse. Any suitable learning algorithm, such as an artificialintelligence algorithm, now known or later developed may be used by thevarious embodiments of the user content preference identification system100.

For example, returning to the hypothetical user's friend who is afootball player, an emotional statement such as, but not limited to,“the user enjoys watching their friend play in a game with the ‘team,’act in a movie, or be a participant or topic of a news cast program ordocumentary” is generated (where the user has previously provided theirfriend's name, and the term “team” is the name of the particular sportsteam that their friend is a member of). The “why” portion of the exampleemotional statement is that the “user enjoys watching their friend.” Theanticipated life events are games, movies, news cast programs ordocumentaries (that their friend is a participant in). An alternativeemotional statement may simply be the user “enjoys seeing their‘friend’.” Emotional statements may be of any suitable length and/orcomplexity.

Here, embodiments have concluded (learned) that the user enjoys watchingtheir close friend perform in a sporting event. During the user queryprocess, the user presumably identified their friend (the candidateobject) as being the cause of their emotional state change. Further, theuser presumably identified their friend by stating their name. Sinceembodiments of the user content preference identification system 100 areconfigured to generate media content event recommendations based onlearned user emotional experiences, embodiments may fairly conclude thatif the named friend is an actor in a movie and/or is the subject orparticipant in a newscast event, then the user will most likely alsolike that type of content. Here, the friend's name and/or team name maybe defined as a life event keyword that is used for searching forcomparable or identical media content event keywords, wherein each of aplurality of media content events include at least one media contentevent keyword that describes a characteristic of the media contentevent.

Returning to the hypothetical example regarding aircraft, embodimentsmay generate an emotional statement that “the user is excited byaircraft” when the user consistently enjoys or becomes excited whenhearing passing aircraft. The learned emotional statement may be furtherreinforced by other real life events wherein the user saw one or moreaircraft, such as when the user has been at an airport, an air show,and/or an aircraft museum. Here, the terms aircraft, airport, flying,etc. may be defined as life event keywords that may be used forsearching for comparable or identical media content event keywords ofmedia content events to identify recommended media content events thatthe user may enjoy.

Conversely, embodiments may generate an emotional statement that “theuser fears flying in aircraft” when the user consistently becomesfearful when hearing passing aircraft. This learned emotional statementmay be further reinforced by other life events wherein the user saw oneor more aircraft, such as when at the airport, an air show, and/or anaircraft museum, or even when the user has previously traveled in anaircraft. Further, the user's commentary provided during the user queryprocess may have indicated a dislike for aircraft and/or flying. Here,the terms aircraft, airport, flying, etc. may be defined as life eventkeywords that may be used for searching for comparable or identicalkeywords of media content events to identify media content events thatthe user may want to avoid.

Summarizing, a plurality of emotional statements are generated for eachuser and are stored into the emotional statements 432 portion of theuser's emotional experiences matrix 430. The emotional statements mayspan a wide range of emotions and a variety of stimuli (viewing aphysical object and/or hearing a particular sound). Emotional statementscontain one or more life event keywords. The emotional statementdescribes an attribute or characteristic of the physical object(s) theuser saw and/or what sound(s) the user heard during the duration 308corresponding to the potential occurrence and/or onset of a change inthe user's emotional state. A life event keyword is a particular term orphrase of an emotional statement that is deemed to be particularlyrelevant to the user's changed emotional state. The life event keywordmay be associated with a physical object seen by or a sound heard by theuser during the life event. After a sufficiently long duration ofmonitoring a user wearing an ESM 102, hundreds or even thousands ofdifferent emotional statements and associated life event keywords may begenerated and saved for each user.

One skilled in the arts appreciates that characteristics and/orattributes describing or pertaining to media content events areavailable from a variety of sources. Typically, information is availablethat includes textual information describing these variouscharacteristics and/or attributes of the media content event. Thetextual information may define one or more media content event keywordsthat described the media content event. The descriptive information mayinclude the title of the media content event, names of actors,producers, and other participants in the production of the media contentevent, identification of set locations, and other related information.Also, the information may include a description of the theme of themedia content event and/or of individual scenes, interchangeablyreferred to herein as story elements and/or story lines. Example mediacontent event keywords include, but are not limited to, actor names,names of other participants, names of set locations, or the like.

This textual descriptive information and/or media content event keywordsmay be created by the producers of the media content event.Alternatively, or additionally, the descriptive information and/or mediacontent event keywords may be generated by operators of the user contentpreference identification system 100 and/or by other interested entitiesfor use by embodiments of the user content preference identificationsystem 100. Alternatively, or additionally, media content event keywordsmay be defined using an artificial intelligence system.

Other supplemental information may be associated with particular mediacontent events. For example, some embodiments may include informationdescribing audience reactions to the media content event and/orindividual scenes. Community members of a social media group may havegenerated commentary (referred to herein as “dubs”) describing theirreaction to and/or view on the media content event and/or one or moreparticular scenes in the media content event. Media content eventkeywords may be generated based on this supplemental information.

After one or more emotional statements have been generated and stored,the processor system 402, executing the content identification logic424, compares the life event keywords of the emotional statements withthe media content event keywords for a plurality of different mediacontent events. When the media content event keywords matches, orsubstantially matches, one or more of the life event keywords generatedfrom an emotional statement of the user, that particular media contentevent may be identified as being of interest (or disinterest, or evendislike) to the user.

An emotional statement may generically describe a life experience, wish,or desire of the user. Such emotional statements may be referred to as“emotional dubs” herein. For example, during a user query process, theuser may indicate that they always wanted to be an actor in a movie. Thegenerated emotional dub, for example, might be the user has a “dream ofbeing an actor.” Story lines associated with media content event may besearched so as to identify media content events having themes and/orstory lines about people who became actors (or people who tried, butfailed, to become actors). Thus, the story line of the media contentevent would be the same, or substantially similar to, the user'semotional dub.

The identifiers of the candidate media content events are saved into therecommended content 434 portion of the user information 428 associatedwith that particular user. Other available information may be optionallystored. For example, many media content events have a brief statementdescribing the thematic content and/or subject of the media contentevent. This supplemental information may be stored with the identifierof the media content event.

Optionally, access information may be saved for each candidate mediacontent event. The access information specifies how and/or when themedia content event is or will be available for consumption by the user.For example, the access information may indicate that the media contentevent is scheduled for a broadcast on a particular channel at a specificfuture date and time. Alternatively, or additionally, the accessinformation may indicate that the media content event is available froman on demand or pay for view type system, and optionally specify theaccess conditions that must be satisfied so that the user can accessthat media content event. Access information may indicate that the mediacontent event is available for purchase on a memory medium (such as acompact disc, digital video disc, or the like) and/or for purchase inelectronic form from a content provider.

Returning to the hypothetical user's friend who is a football player, amedia content event (a football game) between two teams, one of whichthe user's friend is a member of, may be available for viewing (eitherimmediately via on-demand or pay per view system, and/or during anupcoming broadcast). The football game may be identified when the lifeevent keywords (the friend's name or the team name) match the mediacontent event keywords (the names of players and/or teams participatingin the media content event). Thus, embodiments may identify thatparticular media content event (the football game) as a candidate mediacontent event.

As another non-limiting example, the user's friend may be an actor in amovie. Thus, the friend's name (a life event keyword) will match thenames of the actors (media content event keywords) in the movie, andtherefore identify the movie as being a candidate media content event.As yet another example, the user's friend may be the subject of a newscast or documentary. Here, the friend's name will match the names ofindividuals (media content event keywords) who are topics of and/or areparticipants in the news cast or documentary. Accordingly, embodimentsidentify these particular media content events (the news casts ordocumentaries) as candidate media content events.

Returning to the example of the user who enjoys or becomes excited byaircraft, media content events pertaining to aircraft (a media contentevent keyword) may be identified as candidate media content eventsbecause the term “aircraft” (a life event keyword) has been associatedwith the user based on a generated emotional statement for that user.Conversely, if the user fears aircraft and/or flying, media contentevents pertinent to aircraft and/or flying can be identified as beingdisfavored by the user.

After identification of candidate media content events for a particularuser, embodiments of the user content preference identification system100 will generate and communicate emotional-based media content eventrecommendations to the user. Here, the processor system 402, under theexecution of the content recommendation logic 426, generates anemotional-based content recommendation list that is communicated to auser device. The recommended media content event may be indicated to theuser as a media content event that the user is likely to enjoy inresponse to determining that the emotional state of the user isanticipation, joy, trust or another emotion that the user is likely toenjoy when consuming the recommended media content event. Therecommended media content event may be indicated to the user as a mediacontent event that the user is likely to dislike in response todetermining that the emotional state of the user is sadness, disgust,anger, fear that the user is likely to dislike when consuming therecommended media content event. The recommended media content event maybe indicated to the user as a media content event that the user islikely to be disinterested in when determining that the emotional stateof the user is not one of anticipation, joy, trust, sadness, disgust,anger, fear or other strongly felt emotion that the user is likely toexperience when consuming the recommended media content event. That is,a recommendation may be for media content event likes, dislikes and/ordisinterests based on the determined likely user emotional response whenconsuming the media content event.

The emotional-based content recommendation list presents at least alisting of recommended candidate media content events that have beenrecommended for consumption by the user. Other supplemental information,such as supplemental information available from an electronic programguide (EPG) or the like, may also be included in the emotional-basedcontent recommendation list.

Preferably, the emotional-based content recommendation list isgraphically presented on a display of the user's device. Any suitableformat for an emotional-based content recommendation list may be used bythe various embodiments. Further, the emotional-based contentrecommendation list may be presented using an interactive format whereinthe user may schedule a particular one of the recommended media contentevents for recording and/or for immediate presentation. Someemotional-based content recommendation lists will allow the user to seta reminder to view the media content event at a later time and/or at aparticular location and/or particular user device. For example, the usermay interactively make a selection of a particular recommended mediacontent event using their cell phone or smart phone, and then set areminder to watch the selected media content event at their home usingtheir home media device (which may be a set top box or the like). Theuser may even select the media content event for recording by their homemedia device 118 when the media content event is broadcast at a futuredate and time indicated in electronic program guide (EPG) information.

Embodiments may even indicate on the emotional-based contentrecommendation list particular media content events that are expected tobe disfavored by the user. For example, if the user has a fear ofaircraft or flying, then media content events associated with aircraftand/or flying may be indicated to the user because embodiments of theuser content preference identification system 100 has learned that theuser does not like to experience the particular emotion associated withthat object and/or sound. Accordingly, the user appreciates that theymay not want to watch and/or record such aircraft-related media contentevents.

As another example, a particular actor may not be of particular interestto the user. If a media content event with that actor is scheduled for abroadcast at a date and time where the user typically views content, thenotification to the user may provide the opportunity for the user to dosomething else or seek alternative content (e.g., rent a DVD movie orthe like for home viewing during that date and time).

Summarizing, the life event keywords derived from the user's emotionalstatements are compared with media content event keywords for availablemedia content events. Once a match between one or more life eventkeywords and media content event keywords is found, the identified mediacontent events are identified as candidate media content events. Thatis, candidate media content events are identified that are likely toelicit a change in the user's emotional state that is the same as, or issimilar to, the life events that caused a change in the user's emotionalstate. The candidate media content events are then used to generate anemotional-based content recommendation list that identifies thecandidate media content events. Optionally, the emotional-based contentrecommendation list provides access information to the user describinghow and when to access each recommended candidate media content event.Alternatively, or additionally, the emotional-based contentrecommendation list may interactively permit the user to immediatelyaccess a media content event, schedule a media content event forrecording, and/or set a viewing reminder for the media content event.

In an example embodiment, the information in the emotional-based contentrecommendation list may be integrated into an EPG. When the user viewsthe EPG while consuming content, the EPG may indicate recommend mediacontent events that are likely to be of interest (liked or favored) tothe user, may indicate disfavored media content events that are likelyto be disliked by the user, and/or media content events that are likelyto be of no interest (disinterest) to the user. Suitable icons or othergraphical artifacts may be added to a presented EPG to indicate anemotional-based content recommendation. For example, a smiley face iconmay be used to indicate a suggested media content event that the user islikely to enjoy, and an unhappy face icon may be sued to indicate amedia content event that the user is likely to dislike.

In summary, the like, dislike and/or disinterest content recommendationsare based on an anticipated emotional response that is anticipated beexperienced by the user if the user consumes that particular mediacontent event. Such emotional-based content recommendations are incontrast to legacy content recommendation systems that identify mediacontent recommendations based on historical user viewing patterns.

FIG. 5 is a block diagram of an embodiment of the user contentpreference identification system 100 that is operable to control a mediadevice 118, such as, but not limited to, a set top box (STB).Embodiments of the user content preference identification system 100 maybe implemented in other media devices, such as, but not limited to,stereos, surround-sound receivers, radios, televisions (TVs), digitalvideo disc (DVD) players, digital video recorders (DVRs), cellularphones equipped with video functionality, personal device assistants(PDAs), game playing devices, or personal computers (PCs) that areconfigured to present a video-based media content event that is receivedin a media content stream 122.

The exemplary media device 118 is communicatively coupled to a mediapresentation system 120 that includes a visual display device 502, suchas a television (hereafter, generically a TV), and an audio presentationdevice 504, such as a surround sound receiver controlling an audioreproduction device. The video portion of a currently presenting mediacontent event is presented to the user on a display 506 of the visualpresentation device 502. The audio portion of the media content isreproduced as audible sounds by one or more speakers 508 of the audiopresentation device 504. Other types of output devices may also becoupled to the media device 118, including those providing any sort ofstimuli sensible by a human being, such as temperature, vibration andthe like. In some embodiments, the media device 118 and one or more ofthe components of the media presentation system 120 may be integratedinto a single electronic device.

The non-limiting exemplary media device 118 comprises a media contentstream interface 510, a processor system 512, a memory 514, a programbuffer 516, an optional digital video recorder (DVR) 518, a presentationdevice interface 520, a remote interface 522, a communication interface524, and an optional ESM interface 526. The memory 514 comprisesportions for storing the media device logic 528, the electronic programguide (EPG) information 530, an optional browser 532, the portal logic534, and the emotional state change logic 536. In some embodiments, themedia device logic 528, the portal logic 534, and the emotional statechange logic 536 may be integrated together, and/or may be integratedwith other logic. In other embodiments, some or all of these memory andother data manipulation functions may be provided by using a remoteserver or other electronic devices suitably connected via the Internetor otherwise to a client device. Other media devices may include some,or may omit some, of the above-described media processing components.Further, additional components not described herein may be included inalternative embodiments.

The functionality of the media device 118, here a set top box, is nowbroadly described. In a satellite broadcast system, a media contentprovider provides media content that is received in one or more multiplemedia content streams 122 multiplexed together in one or more transportchannels. The transport channels with the media content streams 122 arecommunicated to the media device 118 from a media system sourced from aremote head end facility (not shown) operated by the media contentprovider. The media device 118 is configured to receive one or morebroadcasted satellite signals detected by an antenna (not shown).Non-limiting examples of other media systems that broadcast a mediacontent stream 122 include a cable system, a radio frequency (RF)communication system, and the Internet. Here, broadcasting refers to theprocess of communicating one or more media content streams 122 over abroadcast communication system (not shown) to a plurality of mediadevices 118 that are communicatively coupled to the broadcastcommunication system. Often, the media content is broadcast to hundredsor, or even thousands of, media devices 102 that concurrently receivethe broadcasting media content stream(s) 122.

The one or more media content streams 122 are received by the mediacontent stream interface 510. One or more tuners 510 a in the mediacontent stream interface 510 selectively tune to one of the mediacontent streams 122 in accordance with instructions received from theprocessor system 512. The processor system 512, executing the mediadevice logic 528 and based upon a request for a media content event ofinterest specified by a user, parses out media content associated withthe media content event of interest. The media content event of interestis then assembled into a stream of video and/or audio information whichmay be stored by the program buffer 516 such that the media content canbe streamed out to components of the media presentation system 120, suchas the visual display device 502 and/or the audio presentation device504, via the presentation device interface 520. Alternatively, oradditionally, the parsed out media content may be saved into the DVR 518for later presentation. The DVR 518 may be directly provided in, locallyconnected to, or remotely connected to, the media device 118. Inalternative embodiments, the media content streams 122 may stored forlater decompression, processing and/or decryption.

From time to time, information populating the EPG information 530portion of the memory 514 is communicated to the media device 118, viathe media content stream 122 or via another suitable media. The EPGinformation 530 portion of the memory 514 stores the informationpertaining to the scheduled programming of available media contentevents. The information may include, but is not limited to, a scheduledpresentation start and/or end time, a program channel, and descriptiveinformation. The program's descriptive information may include the titleof the program, names of performers or actors, date of creation, and asummary describing the nature of the program. Any suitable informationmay be included in the program's supplemental information. Theinformation may include one or more media content event keywords, and/ormay be sued to determine media content event keywords. Upon receipt of acommand from the user requesting presentation of an EPG display, theinformation in the EPG information 530 is retrieved, formatted, and thenpresented on the display 506 as an EPG 538.

The exemplary media device 118 is configured to receive commands from auser via a remote control 540. The remote control 540 includes one ormore controllers 542 disposed on the surface of the remote control 540.The user, by actuating one or more of the controllers 542, causes theremote control 540 to generate and transmit commands, via a wirelesssignal 544, to the media device 118. Preferably, each individual one ofthe controllers 542 has a specific predefined function that causes aspecific operation by the media device 118 and/or by components of themedia presentation system 120. The commands communicated from the remotecontrol 540 then control the media device 118 and/or control componentsof the media presentation system 120. The wireless signal 544 may be aninfrared (IR) signal or a radio frequency (RF) signal that is detectableby the remote interface 522.

The processes performed by the media device 118 relating to theprocessing of the received media content stream 122 and communication ofa presentable media content event to the components of the mediapresentation system 106 are generally implemented by the processorsystem 52 while executing the media device logic 528. Thus, the mediadevice 118 may perform a variety of functions related to the processingand presentation of one or more media content events received in themedia content stream 122.

The portal logic 534, when executed by the processor system 512, isconfigured to receive the information acquired by the ESM 102,preferably via the wireless signal 114, at the ESM interface 526.Alternatively, the information from the ESM 102 may be received via awire-based connector at the ESM interface 526. The portal logic 534 isfurther configured to communicate information from the media device 118to the user content preference identification device 106, via thecommunication network 116 that is communicatively coupled to the mediadevice 118 via the communication interface 524. Accordingly, thenon-limiting example media device is operable as a portal 104 a (FIG.1).

The emotional state change logic 536, when executed by the processorsystem 512, is configured to perform a variety of operations pertainingto functions of the user content preference identification system 100.The emotional state change logic 534 may include one or more of theoperations and/or functions performed by the emotional state monitor(ESM) information receiving logic 412, the emotional state changedetermination logic 414, the image frame selection logic 416, the objectidentification logic 418, the user query logic 420, the emotionalstatement generation logic 422, the content identification logic 424,and/or the content recommendation logic 426 implemented in the usercontent preference identification device 106 (FIG. 4). Accordingly,detailed description of the such functions of the emotional state changelogic 534 are not described in detail since such functions are describedin relation to the operation and functionality of the user contentpreference identification device 106.

The exemplary media device 532 includes an optional browser configuredto communicatively couple the media device 118 to a remote site (notshown) and to access supplemental information pertaining to mediacontent events and/or to remotely stored EPG information. In someembodiments, when the emotional-based content recommendation list isgenerated and is presented on the display 506 to the user, the emotionalstate change logic 536 can access the media content event supplementalinformation for incorporation into the emotional-based contentrecommendation list. Alternatively, or additionally, when the EPG 536 isgenerated and then presented on the display 506, information pertainingto the recommendations of the emotional-based content recommendationlist may be integrated into the presented EPG 536.

In some embodiments, the media device receives a continuous stream ofinformation acquired by the ESM 102. In such embodiments, the emotionalstate change logic 534 monitors the brain wave lines 304 to detect apotential occurrence and/or onset of a change in the user's emotionalstate. The received information from the ESM 102 has been stored intothe program buffer 516, into another dedicated buffer memory device (notshown), or into another suitable memory medium. Then, the informationacquired during the duration 314 may be optionally communicated from themedia device 118 to the user content preference identification device106. The emotional-based content recommendation list from the usercontent preference identification device 106 for the particular user ofthe media device 112 may be returned to the media device 112.

In some embodiments, a plurality of different users are associated witha particular media device 112. Accordingly, since each of the differentusers are separately providing input information from their personalESMs 102, individual or unique emotional-based content recommendationlists can be generated for reach individual user. In practice, the mediadevice receives identifying information that identifies each particularuser, and can then present the corresponding information in theemotional-based content recommendation list for that particularidentified user. Some media devices 112 may be configured toautomatically identify particular users.

If a plurality of users are present, some embodiments may be configuredto combine the individual emotional-based content recommendation listfor each user into a composite emotional-based content recommendationlist that indicates recommendations of the plurality of users. Mediacontent events that are commonly liked, disliked, or of disinterest tothe plurality of user's may be presented in a composite emotional-basedcontent recommendation list. Here, only media content events that areliked by all of the present users, disliked by all of the present users,and/or are on no interest to the present users are incorporated into thecomposite emotional-based content recommendation list. An exampleembodiment simply compares the media content events identified in theindividual emotional-based content recommendation lists for each presentuser, and when a match is found for particular media content events,those matching media content events are incorporated into the presentedcomposite emotional-based content recommendation list.

In some embodiments, all media content event recommendations areindicated to the plurality of users in the composite emotional-basedcontent recommendation list. The user's name or other identifier isincluded in the presented composite emotional-based contentrecommendation list so that each different user can identify particularmedia content event recommendations that are directed to their emotionalcharacteristics. Alternatively, or additionally, a color scheme may beused to provide color-based textual information or backgroundsidentifying the recommended media content events, wherein a particulartext color and/or background color is associated with a particular user.

The emotional experiences of the user may be used for other purposes inaddition to generating an emotional-based content recommendation list.In a social community environment, a plurality of users with commonand/or similar experiences may be identified. For example, a pluralityof users who enjoy aircraft may be identified. Here, a plurality ofusers may be identified in the community that have emotional statementwith the same or similar keywords and the same or similar anticipatedemotional responses. A social community environment platform (theprogram and system that manages the social community) supporting thecommunity members may then communicate user identification informationto those identified users (community members) who have common and/orsimilar experiences that are likely to result in common and/or similaremotions. The social community environment platform may then introducethese users having a common emotional characteristic or interest to eachother, and optionally facilitate the formation of a community oflike-minded users.

Additionally, or alternatively, the emotional state information used toidentify media content recommendations that have common and/or similarexperiences may be shared by the social community environment platformwith the identified like-minded user's. That is, if for example acommunity of aircraft enthusiasts has been created on the socialcommunity environment platform, and if a new media content eventpertaining to aircraft becomes available, then all of the user's who aremembers of this community can be advised, through a recommendation, ofthe availability of the new media content event.

Some alternative embodiments may locally store some or all of the userinformation 428 locally in the user's media device 118 and/or in anotherelectronic device of the user in the memory 514 or in another suitablememory medium. Periodic updates may then be received from the usercontent preference identification device 106 and then stored in theuser's media device 118 and/or in the other electronic device.

It should be emphasized that the above-described embodiments of the usercontent preference identification system 100 are merely possibleexamples of implementations of the invention. Many variations andmodifications may be made to the above-described embodiments. All suchmodifications and variations are intended to be included herein withinthe scope of this disclosure and protected by the following claims.

1. A method for recommending media content to a user based on emotionsof the user, the method comprising: receiving Electroencephalography(EEG) information corresponding to a plurality of brain wave lines of auser; receiving image information captured by an image capture devicethat is oriented in a direction of a visual field of view of the userwhile the EEG information is acquired, wherein the EEG information andthe image information are concurrently acquired; identifying anemotional state change of the user based on the received EEGinformation; identifying a candidate object in the captured imageinformation, wherein the candidate object corresponds to a physicalobject seen by the user at a time when the emotional state change of theuser was identified; and identifying one of the plurality of mediacontent events as a recommended media content event based on thecandidate object that was identified in the image information.
 2. Themethod of claim 1, wherein after identifying the at least one candidateobject, the method further comprising: defining an emotional statementbased on the identified emotional state change of the user and theidentified candidate object, wherein the defined emotional statement isa textual statement that describes the identified candidate object, andwherein the emotional statement comprises a keyword that describes theidentified candidate object; and comparing the keyword of the emotionalstatement with a plurality of media content event keywords, wherein eachof the media content event keyword are associated with one or more of aplurality of media content events, wherein one of the plurality of mediacontent events is identified as the recommended media content event inresponse to the media content event keyword matching the keyword of theemotional statement.
 3. The method of claim 1, wherein after identifyingthe emotional state change of the user based on the received EEGinformation, the method further comprising: determining that anemotional state of the user is anticipation when the emotional statechange of the user indicates that the user has an emotional feeling ofexcitement about an event that is going to happen, or is likely tohappen, in the near future as a result of experiencing a first type oflife event; determining that the emotional state of the user is surprisewhen the emotional state change of the user indicates that the user hasan emotional feeling of wonder, astonishment, or amazement as a resultof experiencing a second type of life event that was unanticipated orthat occurred unexpectedly; determining that the emotional state of theuser is joy when the emotional state change of the user indicates thatthe user has an emotional feeling of well-being, success, good fortune,or by the prospect of possessing what one desires as a result ofexperiencing a third type of life event; determining that the emotionalstate of the user is sadness when the emotional state change of the userindicates that the user has an emotional feeling characterized byfeelings of disadvantage, loss, despair, grief, helplessness,disappointment and sorrow as a result of experiencing a fourth type oflife event; determining that the emotional state of the user is disgustwhen the emotional state change of the user indicates that the user hasan emotional feeling of revulsion or profound disapproval aroused bysomething unpleasant or offensive; determining that the emotional stateof the user is trust when the emotional state change of the userindicates that the user has an emotional feeling that someone is goodand honest and will not harm the user, or that someone or something maybe relied upon as a result of experiencing a sixth type of life event;determining that the emotional state of the user is anger when theemotional state change of the user indicates that the user has anemotional feeling characterized by a strong feeling of annoyance,displeasure, or hostility as a result of experiencing a seventh type oflife event; determining that the emotional state of the user is fearwhen the emotional state change of the user indicates that the user hasan emotional feeling of an unpleasant anticipation or awareness ofdanger, pain, or harm as a result of experiencing an eighth type of lifeevent; generating a media content event recommendation, wherein therecommended media content event is indicated to the user as a mediacontent event that the user is likely to enjoy in response todetermining that the emotional state of the user is anticipation, joy,surprise or trust, wherein the recommended media content event isindicated to the user as a media content event that the user is likelyto dislike in response to determining that the emotional state of theuser is sadness, disgust, anger or fear, and wherein the recommendedmedia content event is indicated to the user as a media content eventthat the user is likely to be disinterested in when determining that theemotional state of the user is not one of anticipation, surprise, joy,sadness, disgust, trust, anger, or fear; and presenting the mediacontent event recommendation to the user.
 4. The method of claim 3,further comprising: generating a user query that asks the user tospecify their emotional state during the emotional state change of theuser; comparing the user's specified emotional state to the determinedemotional state; confirming that the determined emotional state iscorrectly determined when the determined emotional state is the same asthe user's specified emotional state; and changing the determinedemotional state to the user's specified emotional state when thedetermined emotional state is different from the user's specifiedemotional state.
 5. The method of claim 1, wherein the candidate objectidentified in the captured image information is a first candidateobject, wherein a second candidate object is also identified in thecaptured image information, and wherein prior to identifying one of theplurality of media content events as the recommended media contentevent, the method further comprising: presenting a first object image tothe user, wherein the first object image includes the first candidateobject; presenting a second object image to the user, wherein the secondobject image includes the second candidate object; and receiving aresponse from the user indicating that viewing one of the firstcandidate object or the second candidate object precipitated theemotional state change of the user, wherein identifying one of theplurality of media content events as the recommended media content eventis based on the indicated one of the first candidate object or thesecond candidate object.
 6. The method of claim 4, further comprising:generating a user query that asks the user to select one of the firstcandidate object or the second candidate object as precipitating thechange in the user's emotional state during the emotional state changeof the user, wherein the response from the user is a selection of one ofthe first candidate object or the second candidate object.
 7. The methodof claim 1, wherein after the candidate object is identified in thecaptured image information and before the recommended media contentevent is identified, the method further comprising: presenting an imageof the candidate object to the user; generating a user query that asksthe user to specify an emotional state that they experienced during theidentified emotional state change of the user; and receiving a userresponse that specified their emotional state that they experiencedduring the emotional state change, wherein one of the plurality of mediacontent events is identified as the recommended media content eventbased on the user specified emotional state that they experienced duringthe emotional state change.
 8. The method of claim 1, wherein after thecandidate object is identified in the captured image information andbefore the recommended media content event is identified, the methodfurther comprising: presenting an image of the candidate object to theuser; generating a user query that asks the user to confirm that thecandidate object caused the identified emotional state change of theuser; and receiving a user response that confirms that the candidateobject caused the identified emotional state change of the user, whereinthe recommended media content event is identified based on the confirmedcandidate object.
 9. The method of claim 8, wherein the candidate objectidentified in the captured image information is a first candidateobject, and wherein the received user response does not confirm that thecandidate object caused the identified emotional state change of theuser, the method further comprising: identifying a second candidateobject in the captured image information when the emotional state changeof the user is identified; generating a user query that asks the user toconfirm that the second candidate object caused the identified emotionalstate change of the user; and receiving a user response that confirmsthat the second candidate object caused the identified emotional statechange of the user, wherein the recommended media content event isidentified based on the confirmed second candidate object.
 10. Themethod of claim 1, further comprising: receiving eye orientationinformation acquired by an eye orientation sensor that senses eyeorientation of the user while the image information is acquired by theimage capture device, wherein the eye orientation information indicatesan orientation of at least one eye of the user, wherein identifying thecandidate object in the captured image information is based on theorientation of the at least one eye of the user that indicates which oneof a plurality of objects the user was looking at that were within thevisual field of view of the user when the image information wasacquired.
 11. The method of claim 1, further comprising: receiving audioinformation acquired by a microphone that includes sounds heard by theuser while the image information is acquired by the image capturedevice; and identifying a candidate sound in the audio information,wherein the candidate sound corresponds to a sound heard by the userduring the emotional state change of the user, wherein identifying oneof the plurality of media content events as a recommended media contentevent is based on the identified candidate sound.
 12. The method ofclaim 11, further comprising: generating a user query that asks the userto confirm that the candidate sound precipitated the emotional statechange of the user; and receiving a user response that confirms that thesound caused the identified emotional state change of the user, whereinthe recommended media content event is identified based on the confirmedsecond candidate object.
 13. The method of claim 1, further comprising:receiving audio information acquired by a microphone that includessounds heard by the user while the image information is acquired by theimage capture device; identifying a candidate sound in the audioinformation, wherein the candidate sound corresponds to a sound heard bythe user during the emotional state change of the user; generating auser query that asks the user to select one of the candidate object orthe candidate sound as precipitating the change in the user's emotionalstate during the emotional state change of the user; and receiving auser response from the user that is a selection of one of the candidateobject or the candidate sound, wherein identifying one of the pluralityof media content events as a recommended media content event is based onthe identified candidate object when the user selects the candidateobject, and wherein identifying one of the plurality of media contentevents as a recommended media content event is based on the identifiedcandidate sound when the user selects the candidate sound.
 14. Themethod of claim 1, wherein after the candidate object is identified inthe captured image information and before the recommended media contentevent is identified, the method further comprising: presenting an imageof the candidate object to the user; generating a user query that asksthe user to specify if an emotional state that they experienced duringthe identified emotional state change of the user occurred during a reallife experience or a content experience, wherein the real liveexperience occurs during a real life event experienced by the user, andwherein the content experience occurs while the user is viewing a mediacontent event; and receiving a user response that specifies one of thereal life experience and the content experience, wherein the recommendedmedia content event is identified based on the user specified one of thereal life experience and the content experience.
 15. The method of claim1, wherein the EEG information includes first time information thatdefines time of acquisition of the EEG information, and wherein theimage information includes second time information that defines time ofacquisition of the image information by the image capture device, themethod further comprising: determining a first time from the first timeinformation, wherein the first time corresponds to an onset of theemotional state change of the user; and determining a second time fromthe second time information, wherein the second time is the same as thefirst time, wherein the candidate object is identified from the imageinformation that was acquired at the second time.
 16. The method ofclaim 15, wherein determining the second time from the second timeinformation further comprises: adding a perception time duration to thefirst time from the first time information to determine the second time,wherein the second time precedes the first time that corresponds to theonset of the emotional state change of the user by the perception timeduration.
 17. The method of claim 1, further comprising: determiningwhether the user was experiencing a real life experience or a contentexperience during the emotional state change of the user, wherein thereal live experience occurs during a real life event experienced by theuser, and wherein the content experience occurs while the user isviewing a media content event; and determining, in response todetermining that the user was experiencing the content experience, anidentifier of the media content event that the user was viewing, whereinthe recommended media content event is identified based on thedetermined identifier of the media content event that the user wasviewing during the emotional state change of the user.
 18. A device,comprising: a transceiver or connector that communicatively couples anemotional state monitor (ESM) to the device, wherein the ESMcommunicates Electroencephalograph (EEG) information corresponding to aplurality of brain wave lines of a user being monitored by the ESM, andwherein the ESM communicates image information captured by an imagecapture device of the ESM that is oriented in a direction of a visualfield of view of the user while the EEG information is acquired, andwherein the EEG information and the image information are concurrentlyacquired; a memory that stores the EEG information and the imageinformation; and a processor system, wherein the processor system isconfigured to: identify an emotional state change of the user based onthe received EEG information; identify a candidate object in thecaptured image information, wherein the candidate object corresponds toa physical object seen by the user at a time when the emotional statechange of the user was identified; and identify one of the plurality ofmedia content events as a recommended media content event based on thecandidate object that was identified in the image information.
 19. Thedevice of claim 18, wherein the processor system is further configuredto: define an emotional statement based on the identified emotionalstate change of the user and the identified candidate object, whereinthe defined emotional statement is a textual statement that describesthe identified candidate object, and wherein the emotional statementcomprises a keyword that describes the identified candidate object;retrieve a plurality of media content event keywords that are associatedwith one or more of a plurality of media content events; and compare thekeyword of the emotional statement with the plurality of media contentevent keywords, wherein each of the media content event keyword, whereinone of the plurality of media content events is identified as therecommended media content event in response to the media content eventkeyword matching the keyword of the emotional statement.
 20. The deviceof claim 18, wherein the processor system is further configured to:receive eye orientation information acquired by an eye orientationsensor of the ESM, wherein the eye orientation sensor senses eyeorientation of the user while the image information is acquired by theimage capture device, wherein the eye orientation information indicatesan orientation of at least one eye of the user, wherein the candidateobject in the captured image information is identified based on theorientation of the at least one eye of the user that indicates which oneof a plurality of objects the user was looking at that were within thevisual field of view of the user when the image information wasacquired.